diff --git a/404.html b/404.html index 75c16707e..d106f40cb 100644 --- a/404.html +++ b/404.html @@ -5,8 +5,8 @@ Page Not Found | CyclOps - - + +
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diff --git a/api/.buildinfo b/api/.buildinfo index d6c0459ef..b5cf5bebb 100644 --- a/api/.buildinfo +++ b/api/.buildinfo @@ -1,4 +1,4 @@ # Sphinx build info version 1 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done. -config: 93c143d5b7029f8140d97be1f5641100 +config: 0555596bae49f971011984d58e3c9fcc tags: 645f666f9bcd5a90fca523b33c5a78b7 diff --git a/api/_modules/cyclops/data/aggregate.html b/api/_modules/cyclops/data/aggregate.html index 825afab2e..f50b196a6 100644 --- a/api/_modules/cyclops/data/aggregate.html +++ b/api/_modules/cyclops/data/aggregate.html @@ -1155,5 +1155,7 @@

Source code for cyclops.data.aggregate

     
     
     
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diff --git a/api/_modules/cyclops/data/features/medical_image.html b/api/_modules/cyclops/data/features/medical_image.html
index cf6e1cc58..4406e3ddc 100644
--- a/api/_modules/cyclops/data/features/medical_image.html
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@@ -681,5 +681,7 @@ 
Source code for cyclops.data.features.medical_image

     
     
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diff --git a/api/_modules/cyclops/data/slicer.html b/api/_modules/cyclops/data/slicer.html
index 7908adfa5..b21940fb4 100644
--- a/api/_modules/cyclops/data/slicer.html
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Source code for cyclops.data.slicer
     
     
     
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diff --git a/api/_modules/cyclops/evaluate/evaluator.html b/api/_modules/cyclops/evaluate/evaluator.html
index 941685880..a0f127410 100644
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@@ -683,5 +683,7 @@ 
Source code for cyclops.evaluate.evaluator
     
     
     
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diff --git a/api/_modules/cyclops/evaluate/fairness/evaluator.html b/api/_modules/cyclops/evaluate/fairness/evaluator.html
index 162f81bda..c9030a206 100644
--- a/api/_modules/cyclops/evaluate/fairness/evaluator.html
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@@ -1351,5 +1351,7 @@ 
Source code for cyclops.evaluate.fairness.evaluator

     
     
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diff --git a/api/_modules/cyclops/evaluate/metrics/accuracy.html b/api/_modules/cyclops/evaluate/metrics/accuracy.html
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--- a/api/_modules/cyclops/evaluate/metrics/accuracy.html
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Source code for cyclops.evaluate.metrics.accuracy

     
     
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diff --git a/api/_modules/cyclops/evaluate/metrics/auroc.html b/api/_modules/cyclops/evaluate/metrics/auroc.html
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--- a/api/_modules/cyclops/evaluate/metrics/auroc.html
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Source code for cyclops.evaluate.metrics.auroc

     
     
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diff --git a/api/_modules/cyclops/evaluate/metrics/average_precision.html b/api/_modules/cyclops/evaluate/metrics/average_precision.html
index 1e5d23870..743d8f6c8 100644
--- a/api/_modules/cyclops/evaluate/metrics/average_precision.html
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Source code for cyclops.evaluate.metrics.average_precision

     
     
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diff --git a/api/_modules/cyclops/evaluate/metrics/f_beta.html b/api/_modules/cyclops/evaluate/metrics/f_beta.html
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Source code for cyclops.evaluate.metrics.f_beta
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diff --git a/api/_modules/cyclops/evaluate/metrics/functional/accuracy.html b/api/_modules/cyclops/evaluate/metrics/functional/accuracy.html
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Source code for cyclops.evaluate.metrics.functional.accuracy

     
     
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diff --git a/api/_modules/cyclops/evaluate/metrics/functional/auroc.html b/api/_modules/cyclops/evaluate/metrics/functional/auroc.html
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Source code for cyclops.evaluate.metrics.functional.auroc

     
     
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diff --git a/api/_modules/cyclops/evaluate/metrics/functional/average_precision.html b/api/_modules/cyclops/evaluate/metrics/functional/average_precision.html
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Source code for cyclops.evaluate.metrics.functional.average_precision

     
     
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diff --git a/api/_modules/cyclops/evaluate/metrics/functional/f_beta.html b/api/_modules/cyclops/evaluate/metrics/functional/f_beta.html
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Source code for cyclops.evaluate.metrics.functional.f_beta

     
     
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diff --git a/api/_modules/cyclops/evaluate/metrics/functional/precision_recall.html b/api/_modules/cyclops/evaluate/metrics/functional/precision_recall.html
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Source code for cyclops.evaluate.metrics.functional.precision_recall

     
     
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diff --git a/api/_modules/cyclops/evaluate/metrics/functional/precision_recall_curve.html b/api/_modules/cyclops/evaluate/metrics/functional/precision_recall_curve.html
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Source code for cyclops.evaluate.metrics.functional.precision_recall_curve
     
     
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diff --git a/api/_modules/cyclops/evaluate/metrics/functional/roc.html b/api/_modules/cyclops/evaluate/metrics/functional/roc.html
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Source code for cyclops.evaluate.metrics.functional.roc

     
     
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diff --git a/api/_modules/cyclops/evaluate/metrics/functional/sensitivity.html b/api/_modules/cyclops/evaluate/metrics/functional/sensitivity.html
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Source code for cyclops.evaluate.metrics.functional.sensitivity

     
     
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diff --git a/api/_modules/cyclops/evaluate/metrics/functional/specificity.html b/api/_modules/cyclops/evaluate/metrics/functional/specificity.html
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Source code for cyclops.evaluate.metrics.functional.specificity

     
     
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diff --git a/api/_modules/cyclops/evaluate/metrics/functional/stat_scores.html b/api/_modules/cyclops/evaluate/metrics/functional/stat_scores.html
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Source code for cyclops.evaluate.metrics.functional.stat_scores

     
     
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diff --git a/api/_modules/cyclops/evaluate/metrics/precision_recall.html b/api/_modules/cyclops/evaluate/metrics/precision_recall.html
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Source code for cyclops.evaluate.metrics.precision_recall

     
     
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diff --git a/api/_modules/cyclops/evaluate/metrics/precision_recall_curve.html b/api/_modules/cyclops/evaluate/metrics/precision_recall_curve.html
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Source code for cyclops.evaluate.metrics.precision_recall_curve

     
     
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diff --git a/api/_modules/cyclops/evaluate/metrics/roc.html b/api/_modules/cyclops/evaluate/metrics/roc.html
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Source code for cyclops.evaluate.metrics.roc

     
     
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diff --git a/api/_modules/cyclops/evaluate/metrics/sensitivity.html b/api/_modules/cyclops/evaluate/metrics/sensitivity.html
index 8c7091445..93eb58c28 100644
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Source code for cyclops.evaluate.metrics.sensitivity

     
     
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diff --git a/api/_modules/cyclops/evaluate/metrics/specificity.html b/api/_modules/cyclops/evaluate/metrics/specificity.html
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Source code for cyclops.evaluate.metrics.specificity

     
     
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diff --git a/api/_modules/cyclops/evaluate/metrics/stat_scores.html b/api/_modules/cyclops/evaluate/metrics/stat_scores.html
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--- a/api/_modules/cyclops/evaluate/metrics/stat_scores.html
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@@ -893,5 +893,7 @@ 
Source code for cyclops.evaluate.metrics.stat_scores

     
     
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diff --git a/api/_modules/cyclops/monitor/clinical_applicator.html b/api/_modules/cyclops/monitor/clinical_applicator.html
index a2cf79342..5b95d2aa2 100644
--- a/api/_modules/cyclops/monitor/clinical_applicator.html
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@@ -949,5 +949,7 @@ 
Source code for cyclops.monitor.clinical_applicator

     
     
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diff --git a/api/_modules/cyclops/monitor/synthetic_applicator.html b/api/_modules/cyclops/monitor/synthetic_applicator.html
index daac2cb8c..d4419b939 100644
--- a/api/_modules/cyclops/monitor/synthetic_applicator.html
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Source code for cyclops.monitor.synthetic_applicator

     
     
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diff --git a/api/_modules/cyclops/report/report.html b/api/_modules/cyclops/report/report.html
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Source code for cyclops.report.report
     
     
     
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diff --git a/api/_modules/cyclops/tasks/classification.html b/api/_modules/cyclops/tasks/classification.html
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Source code for cyclops.tasks.classification

     
     
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diff --git a/api/_modules/index.html b/api/_modules/index.html
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All modules for which code is available

     
     
     
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diff --git a/api/api.html b/api/api.html
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API Reference
     
     
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diff --git a/api/contributing.html b/api/contributing.html
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Coding guidelines
     
     
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Contributing
     
     
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diff --git a/api/evaluation.html b/api/evaluation.html
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Evaluation
     
     
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diff --git a/api/examples/metrics.html b/api/examples/metrics.html
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Preparing Result
 

 

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Preparing Result
 
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Fairness Evaluator
 

 

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[12]:
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Fairness Evaluator
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@@ -1686,5 +1688,7 @@ 
Fairness Evaluator
     
     
+    
+    
     
 
\ No newline at end of file
diff --git a/api/examples/metrics.ipynb b/api/examples/metrics.ipynb
index 3103c3bdc..af8ccacd6 100644
--- a/api/examples/metrics.ipynb
+++ b/api/examples/metrics.ipynb
@@ -14,10 +14,10 @@
    "execution_count": 1,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-04-05T18:56:33.258167Z",
-     "iopub.status.busy": "2024-04-05T18:56:33.257545Z",
-     "iopub.status.idle": "2024-04-05T18:56:37.213100Z",
-     "shell.execute_reply": "2024-04-05T18:56:37.212258Z"
+     "iopub.execute_input": "2024-04-08T13:15:08.129587Z",
+     "iopub.status.busy": "2024-04-08T13:15:08.128767Z",
+     "iopub.status.idle": "2024-04-08T13:15:12.139586Z",
+     "shell.execute_reply": "2024-04-08T13:15:12.138756Z"
     }
    },
    "outputs": [],
@@ -42,10 +42,10 @@
    "execution_count": 2,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-04-05T18:56:37.219037Z",
-     "iopub.status.busy": "2024-04-05T18:56:37.218261Z",
-     "iopub.status.idle": "2024-04-05T18:56:37.234879Z",
-     "shell.execute_reply": "2024-04-05T18:56:37.233966Z"
+     "iopub.execute_input": "2024-04-08T13:15:12.145118Z",
+     "iopub.status.busy": "2024-04-08T13:15:12.144489Z",
+     "iopub.status.idle": "2024-04-08T13:15:12.174600Z",
+     "shell.execute_reply": "2024-04-08T13:15:12.173884Z"
     }
    },
    "outputs": [],
@@ -68,10 +68,10 @@
    "execution_count": 3,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-04-05T18:56:37.240025Z",
-     "iopub.status.busy": "2024-04-05T18:56:37.239679Z",
-     "iopub.status.idle": "2024-04-05T18:56:37.294981Z",
-     "shell.execute_reply": "2024-04-05T18:56:37.294120Z"
+     "iopub.execute_input": "2024-04-08T13:15:12.182760Z",
+     "iopub.status.busy": "2024-04-08T13:15:12.182325Z",
+     "iopub.status.idle": "2024-04-08T13:15:12.246053Z",
+     "shell.execute_reply": "2024-04-08T13:15:12.245412Z"
     }
    },
    "outputs": [
@@ -535,10 +535,10 @@
    "execution_count": 4,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-04-05T18:56:37.345095Z",
-     "iopub.status.busy": "2024-04-05T18:56:37.344520Z",
-     "iopub.status.idle": "2024-04-05T18:56:37.448076Z",
-     "shell.execute_reply": "2024-04-05T18:56:37.447383Z"
+     "iopub.execute_input": "2024-04-08T13:15:12.322106Z",
+     "iopub.status.busy": "2024-04-08T13:15:12.321361Z",
+     "iopub.status.idle": "2024-04-08T13:15:12.436995Z",
+     "shell.execute_reply": "2024-04-08T13:15:12.436307Z"
     }
    },
    "outputs": [],
@@ -581,10 +581,10 @@
    "execution_count": 5,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-04-05T18:56:37.456314Z",
-     "iopub.status.busy": "2024-04-05T18:56:37.455940Z",
-     "iopub.status.idle": "2024-04-05T18:56:37.466057Z",
-     "shell.execute_reply": "2024-04-05T18:56:37.465125Z"
+     "iopub.execute_input": "2024-04-08T13:15:12.442516Z",
+     "iopub.status.busy": "2024-04-08T13:15:12.442087Z",
+     "iopub.status.idle": "2024-04-08T13:15:12.452067Z",
+     "shell.execute_reply": "2024-04-08T13:15:12.451349Z"
     }
    },
    "outputs": [
@@ -617,10 +617,10 @@
    "execution_count": 6,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-04-05T18:56:37.472876Z",
-     "iopub.status.busy": "2024-04-05T18:56:37.472337Z",
-     "iopub.status.idle": "2024-04-05T18:56:37.499046Z",
-     "shell.execute_reply": "2024-04-05T18:56:37.498133Z"
+     "iopub.execute_input": "2024-04-08T13:15:12.457411Z",
+     "iopub.status.busy": "2024-04-08T13:15:12.456971Z",
+     "iopub.status.idle": "2024-04-08T13:15:12.480153Z",
+     "shell.execute_reply": "2024-04-08T13:15:12.479484Z"
     }
    },
    "outputs": [
@@ -666,10 +666,10 @@
    "execution_count": 7,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-04-05T18:56:37.507727Z",
-     "iopub.status.busy": "2024-04-05T18:56:37.507340Z",
-     "iopub.status.idle": "2024-04-05T18:56:37.525719Z",
-     "shell.execute_reply": "2024-04-05T18:56:37.524860Z"
+     "iopub.execute_input": "2024-04-08T13:15:12.487201Z",
+     "iopub.status.busy": "2024-04-08T13:15:12.486802Z",
+     "iopub.status.idle": "2024-04-08T13:15:12.504585Z",
+     "shell.execute_reply": "2024-04-08T13:15:12.503705Z"
     }
    },
    "outputs": [
@@ -710,10 +710,10 @@
    "execution_count": 8,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-04-05T18:56:37.533966Z",
-     "iopub.status.busy": "2024-04-05T18:56:37.533556Z",
-     "iopub.status.idle": "2024-04-05T18:56:37.538925Z",
-     "shell.execute_reply": "2024-04-05T18:56:37.538019Z"
+     "iopub.execute_input": "2024-04-08T13:15:12.511833Z",
+     "iopub.status.busy": "2024-04-08T13:15:12.511154Z",
+     "iopub.status.idle": "2024-04-08T13:15:12.518587Z",
+     "shell.execute_reply": "2024-04-08T13:15:12.517597Z"
     }
    },
    "outputs": [],
@@ -753,10 +753,10 @@
    "execution_count": 9,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-04-05T18:56:37.545824Z",
-     "iopub.status.busy": "2024-04-05T18:56:37.545327Z",
-     "iopub.status.idle": "2024-04-05T18:56:37.555142Z",
-     "shell.execute_reply": "2024-04-05T18:56:37.553719Z"
+     "iopub.execute_input": "2024-04-08T13:15:12.524730Z",
+     "iopub.status.busy": "2024-04-08T13:15:12.524089Z",
+     "iopub.status.idle": "2024-04-08T13:15:12.535020Z",
+     "shell.execute_reply": "2024-04-08T13:15:12.533946Z"
     }
    },
    "outputs": [],
@@ -772,17 +772,17 @@
    "execution_count": 10,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-04-05T18:56:37.562432Z",
-     "iopub.status.busy": "2024-04-05T18:56:37.561781Z",
-     "iopub.status.idle": "2024-04-05T18:56:37.678946Z",
-     "shell.execute_reply": "2024-04-05T18:56:37.678421Z"
+     "iopub.execute_input": "2024-04-08T13:15:12.540485Z",
+     "iopub.status.busy": "2024-04-08T13:15:12.539922Z",
+     "iopub.status.idle": "2024-04-08T13:15:12.759975Z",
+     "shell.execute_reply": "2024-04-08T13:15:12.759284Z"
     }
    },
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "ab67fd4596044307a1ee07be13806415",
+       "model_id": "e6e15cf6670540be97f29e230341d601",
        "version_major": 2,
        "version_minor": 0
       },
@@ -796,7 +796,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "4e35e51809fb47158ffcd06da5771a31",
+       "model_id": "158eaf276e8b4828a46fb7842fe4b2f2",
        "version_major": 2,
        "version_minor": 0
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@@ -810,7 +810,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "7ad5f5435fdd45b9beceea28a7de23cc",
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        "version_major": 2,
        "version_minor": 0
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@@ -847,10 +847,10 @@
    "execution_count": 11,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-04-05T18:56:37.683017Z",
-     "iopub.status.busy": "2024-04-05T18:56:37.682812Z",
-     "iopub.status.idle": "2024-04-05T18:56:37.692110Z",
-     "shell.execute_reply": "2024-04-05T18:56:37.691450Z"
+     "iopub.execute_input": "2024-04-08T13:15:12.764621Z",
+     "iopub.status.busy": "2024-04-08T13:15:12.764114Z",
+     "iopub.status.idle": "2024-04-08T13:15:12.779822Z",
+     "shell.execute_reply": "2024-04-08T13:15:12.778547Z"
     }
    },
    "outputs": [
@@ -868,11 +868,11 @@
        "          0.8235294 , 0.8382353 , 0.85294116, 0.86764705, 0.88235295,\n",
        "          0.89705884, 0.9117647 , 0.9264706 , 0.9411765 , 0.9558824 ,\n",
        "          0.9705882 , 0.9705882 , 0.9852941 , 1.        , 1.        ,\n",
-       "          1.        ], dtype=float32), thresholds=array([1.        , 1.        , 0.99999994, 0.99999982, 0.99999779,\n",
-       "          0.99999678, 0.99999517, 0.99999118, 0.97330832, 0.97148842,\n",
-       "          0.9596203 , 0.94346112, 0.92167199, 0.88678986, 0.74039859,\n",
-       "          0.6472038 , 0.53187394, 0.5       , 0.42952079, 0.38203833,\n",
-       "          0.34660727, 0.28334877, 0.21383326, 0.20890589, 0.00753827,\n",
+       "          1.        ], dtype=float32), thresholds=array([1.        , 1.        , 0.99999988, 0.99999958, 0.99999571,\n",
+       "          0.9999938 , 0.99999082, 0.99998373, 0.96856558, 0.96654218,\n",
+       "          0.95351177, 0.93612415, 0.91314018, 0.8771317 , 0.73206693,\n",
+       "          0.64599931, 0.53249735, 0.5       , 0.4350794 , 0.38956714,\n",
+       "          0.35538796, 0.29455966, 0.22636522, 0.22148167, 0.00967656,\n",
        "          0.        ])),\n",
        "   'BinaryAveragePrecision': 0.7569566,\n",
        "   'BinaryAUROC': 0.475},\n",
@@ -881,16 +881,18 @@
        "   'BinaryRecall': array(0.22222222, dtype=float32),\n",
        "   'BinaryF1Score': array(0.33333334, dtype=float32),\n",
        "   'BinaryROC': ROCCurve(fpr=array([0.    , 0.    , 0.    , 0.0625, 0.125 , 0.1875, 0.1875, 0.1875,\n",
-       "          0.5   , 0.5625, 0.5625, 0.625 , 0.6875, 0.75  , 0.8125, 0.8125,\n",
-       "          0.875 , 0.9375, 1.    ], dtype=float32), tpr=array([0.        , 0.11111111, 0.22222222, 0.22222222, 0.22222222,\n",
+       "          0.4375, 0.5   , 0.5625, 0.5625, 0.625 , 0.6875, 0.75  , 0.8125,\n",
+       "          0.8125, 0.875 , 0.9375, 1.    ], dtype=float32), tpr=array([0.        , 0.11111111, 0.22222222, 0.22222222, 0.22222222,\n",
        "          0.22222222, 0.33333334, 0.44444445, 0.7777778 , 0.7777778 ,\n",
-       "          0.8888889 , 0.8888889 , 0.8888889 , 0.8888889 , 0.8888889 ,\n",
-       "          1.        , 1.        , 1.        , 1.        ], dtype=float32), thresholds=array([1.        , 1.        , 0.9735963 , 0.84236217, 0.44748208,\n",
-       "          0.23282939, 0.22414085, 0.220407  , 0.20862606, 0.20862445,\n",
-       "          0.20862444, 0.20862325, 0.20860244, 0.20852509, 0.20831263,\n",
-       "          0.20601419, 0.2037509 , 0.20052707, 0.03717294], dtype=float32)),\n",
-       "   'BinaryAveragePrecision': 0.59456754,\n",
-       "   'BinaryAUROC': 0.6909722},\n",
+       "          0.7777778 , 0.8888889 , 0.8888889 , 0.8888889 , 0.8888889 ,\n",
+       "          0.8888889 , 1.        , 1.        , 1.        , 1.        ],\n",
+       "         dtype=float32), thresholds=array([1.        , 1.        , 0.96888644, 0.8322844 , 0.45221955,\n",
+       "          0.24512461, 0.2365573 , 0.23286892, 0.2212041 , 0.22120409,\n",
+       "          0.22120251, 0.2212025 , 0.2212013 , 0.22118068, 0.22110394,\n",
+       "          0.22089317, 0.21861212, 0.2163643 , 0.21315964, 0.04399072],\n",
+       "         dtype=float32)),\n",
+       "   'BinaryAveragePrecision': 0.6056786,\n",
+       "   'BinaryAUROC': 0.70138884},\n",
        "  'overall': {'BinaryAccuracy': array(0.75438595, dtype=float32),\n",
        "   'BinaryPrecision': array(0.962963, dtype=float32),\n",
        "   'BinaryRecall': array(0.6666667, dtype=float32),\n",
@@ -901,27 +903,27 @@
        "          0.        , 0.05555556, 0.05555556, 0.05555556, 0.05555556,\n",
        "          0.05555556, 0.11111111, 0.11111111, 0.11111111, 0.11111111,\n",
        "          0.16666667, 0.22222222, 0.22222222, 0.22222222, 0.22222222,\n",
-       "          0.22222222, 0.5       , 0.5555556 , 0.5555556 , 0.6111111 ,\n",
-       "          0.6666667 , 0.7222222 , 0.7777778 , 0.7777778 , 0.8333333 ,\n",
-       "          0.8888889 , 0.9444444 , 1.        ], dtype=float32), tpr=array([0.        , 0.23076923, 0.25641027, 0.2820513 , 0.30769232,\n",
+       "          0.22222222, 0.44444445, 0.5       , 0.5555556 , 0.5555556 ,\n",
+       "          0.6111111 , 0.6666667 , 0.7222222 , 0.7777778 , 0.7777778 ,\n",
+       "          0.8333333 , 0.8888889 , 0.9444444 , 1.        ], dtype=float32), tpr=array([0.        , 0.23076923, 0.25641027, 0.2820513 , 0.30769232,\n",
        "          0.33333334, 0.35897437, 0.3846154 , 0.41025642, 0.43589744,\n",
        "          0.46153846, 0.4871795 , 0.51282054, 0.53846157, 0.5641026 ,\n",
        "          0.5897436 , 0.5897436 , 0.61538464, 0.64102566, 0.6666667 ,\n",
        "          0.6923077 , 0.6923077 , 0.71794873, 0.74358976, 0.7692308 ,\n",
        "          0.7692308 , 0.7692308 , 0.7948718 , 0.82051283, 0.84615386,\n",
-       "          0.8717949 , 0.94871795, 0.94871795, 0.974359  , 0.974359  ,\n",
-       "          0.974359  , 0.974359  , 0.974359  , 1.        , 1.        ,\n",
-       "          1.        , 1.        , 1.        ], dtype=float32), thresholds=array([1.        , 1.        , 0.99999994, 0.9999998 , 0.9999978 ,\n",
-       "          0.9999968 , 0.9999952 , 0.9999912 , 0.9735963 , 0.9733083 ,\n",
-       "          0.9714884 , 0.9596203 , 0.94414216, 0.9434611 , 0.921672  ,\n",
-       "          0.88678986, 0.84236217, 0.7403986 , 0.6472038 , 0.53187394,\n",
-       "          0.5       , 0.44748208, 0.4295208 , 0.38203833, 0.34660727,\n",
-       "          0.28334877, 0.23282939, 0.22414085, 0.220407  , 0.21383326,\n",
-       "          0.20890589, 0.20862606, 0.20862445, 0.20862444, 0.20862325,\n",
-       "          0.20860244, 0.20852509, 0.20831263, 0.20601419, 0.2037509 ,\n",
-       "          0.20052707, 0.03717294, 0.00753827], dtype=float32)),\n",
-       "   'BinaryAveragePrecision': 0.9527409,\n",
-       "   'BinaryAUROC': 0.90099716}}}"
+       "          0.8717949 , 0.94871795, 0.94871795, 0.94871795, 0.974359  ,\n",
+       "          0.974359  , 0.974359  , 0.974359  , 0.974359  , 1.        ,\n",
+       "          1.        , 1.        , 1.        , 1.        ], dtype=float32), thresholds=array([1.        , 1.        , 0.9999999 , 0.9999996 , 0.9999957 ,\n",
+       "          0.9999938 , 0.9999908 , 0.9999837 , 0.96888644, 0.9685656 ,\n",
+       "          0.9665422 , 0.9535118 , 0.9368503 , 0.93612415, 0.9131402 ,\n",
+       "          0.8771317 , 0.8322844 , 0.7320669 , 0.6459993 , 0.53249735,\n",
+       "          0.5       , 0.45221955, 0.4350794 , 0.38956714, 0.35538796,\n",
+       "          0.29455966, 0.24512461, 0.2365573 , 0.23286892, 0.22636522,\n",
+       "          0.22148167, 0.2212041 , 0.22120409, 0.22120251, 0.2212025 ,\n",
+       "          0.2212013 , 0.22118068, 0.22110394, 0.22089317, 0.21861212,\n",
+       "          0.2163643 , 0.21315964, 0.04399072, 0.00967656], dtype=float32)),\n",
+       "   'BinaryAveragePrecision': 0.95411587,\n",
+       "   'BinaryAUROC': 0.9031339}}}"
       ]
      },
      "execution_count": 11,
@@ -947,10 +949,10 @@
    "execution_count": 12,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2024-04-05T18:56:37.696599Z",
-     "iopub.status.busy": "2024-04-05T18:56:37.696256Z",
-     "iopub.status.idle": "2024-04-05T18:56:39.090094Z",
-     "shell.execute_reply": "2024-04-05T18:56:39.089260Z"
+     "iopub.execute_input": "2024-04-08T13:15:12.784389Z",
+     "iopub.status.busy": "2024-04-08T13:15:12.783760Z",
+     "iopub.status.idle": "2024-04-08T13:15:14.278157Z",
+     "shell.execute_reply": "2024-04-08T13:15:14.277498Z"
     }
    },
    "outputs": [
@@ -958,13 +960,13 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2024-04-05 14:56:37,699 \u001b[1;33mWARNING\u001b[0m cyclops.evaluate.fairness.evaluator - The number of unique values for the group is greater than 50. This may take a long time to compute. Consider binning the values into fewer groups.\n"
+      "2024-04-08 09:15:12,788 \u001b[1;33mWARNING\u001b[0m cyclops.evaluate.fairness.evaluator - The number of unique values for the group is greater than 50. This may take a long time to compute. Consider binning the values into fewer groups.\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "f3fdfec9c39c4244afed521ceff34df1",
+       "model_id": "7aae8bd849364a6c8ca2561bfbed2814",
        "version_major": 2,
        "version_minor": 0
       },
@@ -978,7 +980,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "24cd8e8d7bdc4b0fab043848871d54ea",
+       "model_id": "663cf39622644e72b2c99331cf288703",
        "version_major": 2,
        "version_minor": 0
       },
@@ -992,7 +994,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "e6e8aa6abcee4705a780cedcc061529d",
+       "model_id": "06da39a8d9c94603a534ff8198df685a",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1006,7 +1008,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "1fe5dd53e9b04e86926eb9948e0e81f9",
+       "model_id": "4e401890558e4b31a6aeef24f903e4b6",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1027,7 +1029,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "1f201a8784194ec1afbaa7d35e37fc90",
+       "model_id": "6c56999854a14895a9c24a92feffbdaa",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1041,7 +1043,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "8f152ac5922a4366b04e5533ef599b28",
+       "model_id": "fd41ae660601409995e1b4e882ad7adb",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1055,7 +1057,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "6af5e3b1bcc34c48b1588be1f7ae483a",
+       "model_id": "fcbf28e1d84542c89a81690b3facabbb",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1069,7 +1071,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "3f61a43e43544b76b5f63faedc517dbb",
+       "model_id": "3720b058604143e69e3fe32eb7e9710d",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1083,7 +1085,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "73b1976203c84bae84495e215b54f220",
+       "model_id": "68c83da337f84b0e81c431ab67382669",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1097,7 +1099,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "10ae7a438e0a4cb0b8eb7ac3064b1b3c",
+       "model_id": "145da6e5e2f44ac49674d59776c14454",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1111,7 +1113,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "4a28dc2b91564639818eaad3ab80ffbe",
+       "model_id": "c0261beabfe04ed39b5390448e73e142",
        "version_major": 2,
        "version_minor": 0
       },
@@ -1125,7 +1127,7 @@
     {
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Generate Source/Target Dataset for Experiments (1-2)": [[62, "Example-1.-Generate-Source/Target-Dataset-for-Experiments-(1-2)"]], "Example 2. Sensitivity test experiment with 3 dimensionality reduction techniques": [[62, "Example-2.-Sensitivity-test-experiment-with-3-dimensionality-reduction-techniques"]], "Example 3. Sensitivity test experiment with models trained on different datasets": [[62, "Example-3.-Sensitivity-test-experiment-with-models-trained-on-different-datasets"]], "Example 4. Sensitivity test experiment with different clinical shifts": [[62, "Example-4.-Sensitivity-test-experiment-with-different-clinical-shifts"]], "Example 5. Rolling window experiment with synthetic timestamps using biweekly window": [[62, "Example-5.-Rolling-window-experiment-with-synthetic-timestamps-using-biweekly-window"]], "Prolonged Length of Stay Prediction": [[63, "Prolonged-Length-of-Stay-Prediction"]], "Data Querying": [[63, "Data-Querying"]], "Compute length of stay (labels)": [[63, "Compute-length-of-stay-(labels)"]], "Length of stay distribution": [[63, "Length-of-stay-distribution"]], "monitor API": [[64, "monitor-api"]], "Example use cases": [[65, "example-use-cases"]], "Tabular data": [[65, "tabular-data"]], "Kaggle Heart Failure Prediction": [[65, "kaggle-heart-failure-prediction"]], "MIMICIV Mortality Prediction": [[65, "mimiciv-mortality-prediction"]], "Synthea Prolonged Length of Stay Prediction": [[65, "synthea-prolonged-length-of-stay-prediction"]], "Image data": [[65, "image-data"]], "NIH Chest X-ray classification": [[65, "nih-chest-x-ray-classification"]], "User Guide": [[66, "user-guide"]]}, "indexentries": {"cyclops.data.aggregate": [[9, "module-cyclops.data.aggregate"]], "module": [[9, "module-cyclops.data.aggregate"], [13, "module-cyclops.data.features.medical_image"], [15, "module-cyclops.data.slicer"], [25, "module-cyclops.monitor.clinical_applicator"], [27, "module-cyclops.monitor.synthetic_applicator"], [34, "module-cyclops.report.report"], [36, "module-cyclops.tasks.classification"], [39, "module-cyclops.data"], [39, "module-cyclops.data.features"], [40, "module-cyclops.monitor"], [41, "module-cyclops.report"], [42, "module-cyclops.tasks"]], "aggregator (class in cyclops.data.aggregate)": [[10, "cyclops.data.aggregate.Aggregator"]], "__init__() (aggregator method)": [[10, "cyclops.data.aggregate.Aggregator.__init__"]], "agg_by (aggregator attribute)": [[10, "cyclops.data.aggregate.Aggregator.agg_by"]], "agg_meta_for (aggregator attribute)": [[10, "cyclops.data.aggregate.Aggregator.agg_meta_for"]], "aggfuncs (aggregator attribute)": [[10, "cyclops.data.aggregate.Aggregator.aggfuncs"]], "fit() (aggregator method)": [[10, "cyclops.data.aggregate.Aggregator.fit"]], "fit_transform() (aggregator method)": [[10, "cyclops.data.aggregate.Aggregator.fit_transform"]], "imputer (aggregator attribute)": [[10, "cyclops.data.aggregate.Aggregator.imputer"]], "num_timesteps (aggregator attribute)": [[10, "cyclops.data.aggregate.Aggregator.num_timesteps"]], "set_output() (aggregator method)": [[10, "cyclops.data.aggregate.Aggregator.set_output"]], "time_by (aggregator attribute)": [[10, "cyclops.data.aggregate.Aggregator.time_by"]], "timestamp_col (aggregator attribute)": [[10, "cyclops.data.aggregate.Aggregator.timestamp_col"]], "timestep_size (aggregator attribute)": [[10, "cyclops.data.aggregate.Aggregator.timestep_size"]], "transform() (aggregator method)": [[10, "cyclops.data.aggregate.Aggregator.transform"]], "window_duration (aggregator attribute)": [[10, "cyclops.data.aggregate.Aggregator.window_duration"]], "window_start_time (aggregator attribute)": [[10, "cyclops.data.aggregate.Aggregator.window_start_time"]], "window_stop_time (aggregator attribute)": [[10, "cyclops.data.aggregate.Aggregator.window_stop_time"]], "window_times (aggregator attribute)": [[10, "cyclops.data.aggregate.Aggregator.window_times"]], "tabular_as_aggregated() (in module cyclops.data.aggregate)": [[11, "cyclops.data.aggregate.tabular_as_aggregated"]], "timestamp_ffill_agg() (in module cyclops.data.aggregate)": [[12, "cyclops.data.aggregate.timestamp_ffill_agg"]], "cyclops.data.features.medical_image": [[13, "module-cyclops.data.features.medical_image"]], "medicalimage (class in cyclops.data.features.medical_image)": [[14, "cyclops.data.features.medical_image.MedicalImage"]], "__call__() (medicalimage method)": [[14, "cyclops.data.features.medical_image.MedicalImage.__call__"]], "cast_storage() (medicalimage method)": [[14, "cyclops.data.features.medical_image.MedicalImage.cast_storage"]], "decode_example() (medicalimage method)": 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"overall() (in module cyclops.data.slicer)": [[24, "cyclops.data.slicer.overall"]], "cyclops.monitor.clinical_applicator": [[25, "module-cyclops.monitor.clinical_applicator"]], "clinicalshiftapplicator (class in cyclops.monitor.clinical_applicator)": [[26, "cyclops.monitor.clinical_applicator.ClinicalShiftApplicator"]], "age() (clinicalshiftapplicator method)": [[26, "cyclops.monitor.clinical_applicator.ClinicalShiftApplicator.age"]], "apply_shift() (clinicalshiftapplicator method)": [[26, "cyclops.monitor.clinical_applicator.ClinicalShiftApplicator.apply_shift"]], "custom() (clinicalshiftapplicator method)": [[26, "cyclops.monitor.clinical_applicator.ClinicalShiftApplicator.custom"]], "hospital_type() (clinicalshiftapplicator method)": [[26, "cyclops.monitor.clinical_applicator.ClinicalShiftApplicator.hospital_type"]], "month() (clinicalshiftapplicator method)": [[26, "cyclops.monitor.clinical_applicator.ClinicalShiftApplicator.month"]], "sex() (clinicalshiftapplicator method)": [[26, 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"cyclops.monitor.synthetic_applicator.feature_swap_shift"]], "gaussian_noise_shift() (in module cyclops.monitor.synthetic_applicator)": [[32, "cyclops.monitor.synthetic_applicator.gaussian_noise_shift"]], "knockout_shift() (in module cyclops.monitor.synthetic_applicator)": [[33, "cyclops.monitor.synthetic_applicator.knockout_shift"]], "cyclops.report.report": [[34, "module-cyclops.report.report"]], "modelcardreport (class in cyclops.report.report)": [[35, "cyclops.report.report.ModelCardReport"]], "export() (modelcardreport method)": [[35, "cyclops.report.report.ModelCardReport.export"]], "from_json_file() (modelcardreport class method)": [[35, "cyclops.report.report.ModelCardReport.from_json_file"]], "log_citation() (modelcardreport method)": [[35, "cyclops.report.report.ModelCardReport.log_citation"]], "log_dataset() (modelcardreport method)": [[35, "cyclops.report.report.ModelCardReport.log_dataset"]], "log_descriptor() (modelcardreport method)": [[35, 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"multilabelprecisionrecallcurve (class in cyclops.evaluate.metrics)": [[52, "cyclops.evaluate.metrics.MultilabelPrecisionRecallCurve"]], "precisionrecallcurve (class in cyclops.evaluate.metrics)": [[52, "cyclops.evaluate.metrics.PrecisionRecallCurve"]], "multiclass_precision_recall_curve() (in module cyclops.evaluate.metrics.functional.precision_recall_curve)": [[52, "cyclops.evaluate.metrics.functional.precision_recall_curve.multiclass_precision_recall_curve"]], "multilabel_precision_recall_curve() (in module cyclops.evaluate.metrics.functional.precision_recall_curve)": [[52, "cyclops.evaluate.metrics.functional.precision_recall_curve.multilabel_precision_recall_curve"]], "precision_recall_curve() (in module cyclops.evaluate.metrics.functional.precision_recall_curve)": [[52, "cyclops.evaluate.metrics.functional.precision_recall_curve.precision_recall_curve"]], "binaryrecall (class in cyclops.evaluate.metrics)": [[53, "cyclops.evaluate.metrics.BinaryRecall"]], "multiclassrecall (class 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\ No newline at end of file
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"cyclops.evaluate.metrics.MulticlassSensitivity"]], "multilabelsensitivity (class in cyclops.evaluate.metrics)": [[55, "cyclops.evaluate.metrics.MultilabelSensitivity"]], "sensitivity (class in cyclops.evaluate.metrics)": [[55, "cyclops.evaluate.metrics.Sensitivity"]], "binary_sensitivity() (in module cyclops.evaluate.metrics.functional.sensitivity)": [[55, "cyclops.evaluate.metrics.functional.sensitivity.binary_sensitivity"]], "multiclass_sensitivity() (in module cyclops.evaluate.metrics.functional.sensitivity)": [[55, "cyclops.evaluate.metrics.functional.sensitivity.multiclass_sensitivity"]], "multilabel_sensitivity() (in module cyclops.evaluate.metrics.functional.sensitivity)": [[55, "cyclops.evaluate.metrics.functional.sensitivity.multilabel_sensitivity"]], "sensitivity() (in module cyclops.evaluate.metrics.functional.sensitivity)": [[55, "cyclops.evaluate.metrics.functional.sensitivity.sensitivity"]], "binaryspecificity (class in cyclops.evaluate.metrics)": [[56, "cyclops.evaluate.metrics.BinarySpecificity"]], "multiclassspecificity (class in cyclops.evaluate.metrics)": [[56, "cyclops.evaluate.metrics.MulticlassSpecificity"]], "multilabelspecificity (class in cyclops.evaluate.metrics)": [[56, "cyclops.evaluate.metrics.MultilabelSpecificity"]], "specificity (class in cyclops.evaluate.metrics)": [[56, "cyclops.evaluate.metrics.Specificity"]], "binary_specificity() (in module cyclops.evaluate.metrics.functional.specificity)": [[56, "cyclops.evaluate.metrics.functional.specificity.binary_specificity"]], "multiclass_specificity() (in module cyclops.evaluate.metrics.functional.specificity)": [[56, "cyclops.evaluate.metrics.functional.specificity.multiclass_specificity"]], "multilabel_specificity() (in module cyclops.evaluate.metrics.functional.specificity)": [[56, "cyclops.evaluate.metrics.functional.specificity.multilabel_specificity"]], "specificity() (in module cyclops.evaluate.metrics.functional.specificity)": [[56, "cyclops.evaluate.metrics.functional.specificity.specificity"]], "binarystatscores (class in cyclops.evaluate.metrics)": [[57, "cyclops.evaluate.metrics.BinaryStatScores"]], "multiclassstatscores (class in cyclops.evaluate.metrics)": [[57, "cyclops.evaluate.metrics.MulticlassStatScores"]], "multilabelstatscores (class in cyclops.evaluate.metrics)": [[57, "cyclops.evaluate.metrics.MultilabelStatScores"]], "statscores (class in cyclops.evaluate.metrics)": [[57, "cyclops.evaluate.metrics.StatScores"]], "binary_stat_scores() (in module cyclops.evaluate.metrics.functional.stat_scores)": [[57, "cyclops.evaluate.metrics.functional.stat_scores.binary_stat_scores"]], "multiclass_stat_scores() (in module cyclops.evaluate.metrics.functional.stat_scores)": [[57, "cyclops.evaluate.metrics.functional.stat_scores.multiclass_stat_scores"]], "multilabel_stat_scores() (in module cyclops.evaluate.metrics.functional.stat_scores)": [[57, "cyclops.evaluate.metrics.functional.stat_scores.multilabel_stat_scores"]], "stat_scores() (in module cyclops.evaluate.metrics.functional.stat_scores)": [[57, "cyclops.evaluate.metrics.functional.stat_scores.stat_scores"]]}})
\ No newline at end of file
diff --git a/api/tutorials.html b/api/tutorials.html
index bebe6d9a6..eda183b9d 100644
--- a/api/tutorials.html
+++ b/api/tutorials.html
@@ -409,5 +409,7 @@ 
Tutorials
     
     
+    
+    
     
 
\ No newline at end of file
diff --git a/api/tutorials/kaggle/heart_failure_prediction.html b/api/tutorials/kaggle/heart_failure_prediction.html
index de81df1aa..7988a037a 100644
--- a/api/tutorials/kaggle/heart_failure_prediction.html
+++ b/api/tutorials/kaggle/heart_failure_prediction.html
@@ -417,7 +417,7 @@ 
Data Loading
 
-2024-04-05 14:56:53,487 INFO cyclops.utils.file - Loading DataFrame from ./data/heart.csv
+2024-04-08 09:15:28,882 INFO cyclops.utils.file - Loading DataFrame from ./data/heart.csv
@@ -499,9 +499,9 @@

Sex values

-
+
@@ -999,7 +999,7 @@

Training 
-2024-04-05 14:57:00,475 INFO cyclops.models.wrappers.sk_model - Best alpha: 0.001
+2024-04-08 09:15:36,311 INFO cyclops.models.wrappers.sk_model - Best alpha: 0.001
@@ -1007,7 +1007,7 @@

Training 

-2024-04-05 14:57:00,475 INFO cyclops.models.wrappers.sk_model - Best eta0: 0.01
+2024-04-08 09:15:36,312 INFO cyclops.models.wrappers.sk_model - Best eta0: 0.01
@@ -1015,7 +1015,7 @@

Training 

-2024-04-05 14:57:00,476 INFO cyclops.models.wrappers.sk_model - Best learning_rate: adaptive
+2024-04-08 09:15:36,313 INFO cyclops.models.wrappers.sk_model - Best learning_rate: adaptive
@@ -1489,7 +1489,7 @@

Prediction

-
+

@@ -1607,61 +1607,61 @@

Evaluation
-
+
-
+
-
+
-
+
-
+
-
+
-
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-
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-
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-
+
[36]:
@@ -1690,31 +1690,31 @@ 
Evaluation
-
+
-
+
-
+
-
+
-
+

Log the performance metrics to the report.

We can add a performance metric to the model card using the log_performance_metric method, which expects a dictionary where the keys are in the following format: slice_name/metric_name. For instance, overall/accuracy.

@@ -1831,9 +1831,9 @@

Evaluation
-

@@ -2755,5 +2755,7 @@

Report Generation + + \ No newline at end of file diff --git a/api/tutorials/kaggle/heart_failure_prediction.ipynb b/api/tutorials/kaggle/heart_failure_prediction.ipynb index b22c1d84f..da04de73b 100644 --- a/api/tutorials/kaggle/heart_failure_prediction.ipynb +++ b/api/tutorials/kaggle/heart_failure_prediction.ipynb @@ -21,10 +21,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2024-04-05T18:56:48.507754Z", - "iopub.status.busy": "2024-04-05T18:56:48.507072Z", - "iopub.status.idle": "2024-04-05T18:56:53.025098Z", - "shell.execute_reply": "2024-04-05T18:56:53.024330Z" + "iopub.execute_input": "2024-04-08T13:15:23.796579Z", + "iopub.status.busy": "2024-04-08T13:15:23.795989Z", + "iopub.status.idle": "2024-04-08T13:15:28.437851Z", + "shell.execute_reply": "2024-04-08T13:15:28.437083Z" }, "tags": [] }, @@ -91,10 +91,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2024-04-05T18:56:53.030851Z", - "iopub.status.busy": "2024-04-05T18:56:53.030267Z", - "iopub.status.idle": "2024-04-05T18:56:53.034955Z", - "shell.execute_reply": "2024-04-05T18:56:53.034084Z" + "iopub.execute_input": "2024-04-08T13:15:28.443107Z", + "iopub.status.busy": "2024-04-08T13:15:28.442672Z", + "iopub.status.idle": "2024-04-08T13:15:28.446676Z", + "shell.execute_reply": "2024-04-08T13:15:28.446044Z" } }, "outputs": [], @@ -114,10 +114,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2024-04-05T18:56:53.042012Z", - "iopub.status.busy": "2024-04-05T18:56:53.040908Z", - "iopub.status.idle": "2024-04-05T18:56:53.047778Z", - "shell.execute_reply": "2024-04-05T18:56:53.046758Z" + "iopub.execute_input": "2024-04-08T13:15:28.451629Z", + "iopub.status.busy": "2024-04-08T13:15:28.451277Z", + "iopub.status.idle": "2024-04-08T13:15:28.455291Z", + "shell.execute_reply": "2024-04-08T13:15:28.454452Z" }, "tags": [] }, @@ -143,10 +143,10 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2024-04-05T18:56:53.053691Z", - "iopub.status.busy": "2024-04-05T18:56:53.053120Z", - "iopub.status.idle": "2024-04-05T18:56:53.481096Z", - "shell.execute_reply": "2024-04-05T18:56:53.480324Z" + "iopub.execute_input": "2024-04-08T13:15:28.459691Z", + "iopub.status.busy": "2024-04-08T13:15:28.459295Z", + "iopub.status.idle": "2024-04-08T13:15:28.869769Z", + "shell.execute_reply": "2024-04-08T13:15:28.868281Z" }, "tags": [] }, @@ -166,10 +166,10 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2024-04-05T18:56:53.486188Z", - "iopub.status.busy": "2024-04-05T18:56:53.485782Z", - "iopub.status.idle": "2024-04-05T18:56:53.506725Z", - "shell.execute_reply": "2024-04-05T18:56:53.506024Z" + "iopub.execute_input": "2024-04-08T13:15:28.879473Z", + "iopub.status.busy": "2024-04-08T13:15:28.878804Z", + "iopub.status.idle": "2024-04-08T13:15:28.904681Z", + "shell.execute_reply": "2024-04-08T13:15:28.903651Z" }, "tags": [] }, @@ -178,7 +178,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-05 14:56:53,487 \u001b[1;37mINFO\u001b[0m cyclops.utils.file - Loading DataFrame from ./data/heart.csv\n" + "2024-04-08 09:15:28,882 \u001b[1;37mINFO\u001b[0m cyclops.utils.file - Loading DataFrame from ./data/heart.csv\n" ] }, { @@ -234,10 +234,10 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2024-04-05T18:56:53.512044Z", - "iopub.status.busy": "2024-04-05T18:56:53.511670Z", - "iopub.status.idle": "2024-04-05T18:56:53.766870Z", - "shell.execute_reply": "2024-04-05T18:56:53.764532Z" + "iopub.execute_input": "2024-04-08T13:15:28.909040Z", + "iopub.status.busy": "2024-04-08T13:15:28.908667Z", + "iopub.status.idle": "2024-04-08T13:15:29.560870Z", + "shell.execute_reply": "2024-04-08T13:15:29.560155Z" }, "tags": [] }, @@ -2045,9 +2045,9 @@ } }, "text/html": [ - "
+
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Graphics

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Graphics

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Graphics

-
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@@ -1798,7 +1798,7 @@

Version

- Date: 2024-04-05 + Date: 2024-04-08
@@ -2016,18 +2016,14 @@

Model Parameters

-
-

Shuffle

- True -
-

Alpha

- 0.001 +

Penalty

+ l2
@@ -2035,8 +2031,8 @@

Alpha

-

Power_t

- 0.5 +

L1_ratio

+ 0.15
@@ -2044,8 +2040,8 @@

Power_t

-

Verbose

- 0 +

Max_iter

+ 1000
@@ -2053,8 +2049,8 @@

Verbose

-

Loss

- log_loss +

Class_weight

+ balanced
@@ -2062,8 +2058,8 @@

Loss

-

N_iter_no_change

- 5 +

Learning_rate

+ adaptive
@@ -2071,8 +2067,8 @@

N_iter_no_change

-

Eta0

- 0.01 +

Loss

+ log_loss
@@ -2080,8 +2076,8 @@

Eta0

-

Learning_rate

- adaptive +

Epsilon

+ 0.1
@@ -2089,8 +2085,8 @@

Learning_rate

-

Max_iter

- 1000 +

Average

+ False
@@ -2098,8 +2094,8 @@

Max_iter

-

Random_state

- 123 +

Eta0

+ 0.01
@@ -2107,8 +2103,8 @@

Random_state

-

Epsilon

- 0.1 +

Alpha

+ 0.001
@@ -2116,7 +2112,7 @@

Epsilon

-

Fit_intercept

+

Early_stopping

True
@@ -2125,7 +2121,7 @@

Fit_intercept

-

Average

+

Warm_start

False
@@ -2134,8 +2130,8 @@

Average

-

Validation_fraction

- 0.1 +

N_iter_no_change

+ 5
@@ -2143,7 +2139,7 @@

Validation_fraction

-

Early_stopping

+

Shuffle

True
@@ -2151,14 +2147,18 @@

Early_stopping

+
+

Verbose

+ 0 +
-

Class_weight

- balanced +

Fit_intercept

+ True
@@ -2166,8 +2166,8 @@

Class_weight

-

Penalty

- l2 +

Power_t

+ 0.5
@@ -2175,8 +2175,8 @@

Penalty

-

L1_ratio

- 0.15 +

Random_state

+ 123
@@ -2184,8 +2184,8 @@

L1_ratio

-

Tol

- 0.001 +

Validation_fraction

+ 0.1
@@ -2193,8 +2193,8 @@

Tol

-

Warm_start

- False +

Tol

+ 0.001
diff --git a/api/tutorials/mimiciv/mortality_prediction.html b/api/tutorials/mimiciv/mortality_prediction.html index d848738b1..70b552258 100644 --- a/api/tutorials/mimiciv/mortality_prediction.html +++ b/api/tutorials/mimiciv/mortality_prediction.html @@ -570,7 +570,7 @@

Compute mortality (labels) 
-2024-04-05 14:57:15,445 INFO cycquery.orm    - Database setup, ready to run queries!
+2024-04-08 09:15:53,763 INFO cycquery.orm    - Database setup, ready to run queries!
@@ -578,7 +578,7 @@

Compute mortality (labels) 
-2024-04-05 14:57:22,990 INFO cycquery.orm    - Query returned successfully!
+2024-04-08 09:16:01,365 INFO cycquery.orm    - Query returned successfully!

@@ -586,7 +586,7 @@

Compute mortality (labels) 
-2024-04-05 14:57:22,991 INFO cycquery.utils.profile - Finished executing function run_query in 5.434670 s
+2024-04-08 09:16:01,366 INFO cycquery.utils.profile - Finished executing function run_query in 5.358807 s

@@ -605,7 +605,7 @@

Compute mortality (labels) 
-2024-04-05 14:57:53,105 INFO cycquery.orm    - Query returned successfully!
+2024-04-08 09:16:15,493 INFO cycquery.orm    - Query returned successfully!

@@ -613,7 +613,7 @@

Compute mortality (labels) 
-2024-04-05 14:57:53,106 INFO cycquery.utils.profile - Finished executing function run_query in 29.359461 s
+2024-04-08 09:16:15,494 INFO cycquery.utils.profile - Finished executing function run_query in 13.368719 s

@@ -685,9 +685,9 @@

Drop NaNs based on the

-
+
@@ -1165,7 +1165,7 @@

Training 
-2024-04-05 15:01:23,813 INFO cyclops.models.wrappers.sk_model - Best reg_lambda: 0
+2024-04-08 09:18:04,778 INFO cyclops.models.wrappers.sk_model - Best reg_lambda: 1
@@ -1173,7 +1173,7 @@

Training 

-2024-04-05 15:01:23,814 INFO cyclops.models.wrappers.sk_model - Best n_estimators: 250
+2024-04-08 09:18:04,779 INFO cyclops.models.wrappers.sk_model - Best n_estimators: 250
@@ -1181,7 +1181,7 @@

Training 

-2024-04-05 15:01:23,814 INFO cyclops.models.wrappers.sk_model - Best max_depth: 5
+2024-04-08 09:18:04,779 INFO cyclops.models.wrappers.sk_model - Best max_depth: 5
@@ -1189,7 +1189,7 @@

Training 

-2024-04-05 15:01:23,814 INFO cyclops.models.wrappers.sk_model - Best learning_rate: 0.1
+2024-04-08 09:18:04,779 INFO cyclops.models.wrappers.sk_model - Best learning_rate: 0.1
@@ -1197,7 +1197,7 @@

Training 

-2024-04-05 15:01:23,815 INFO cyclops.models.wrappers.sk_model - Best gamma: 0
+2024-04-08 09:18:04,780 INFO cyclops.models.wrappers.sk_model - Best gamma: 2
@@ -1205,7 +1205,7 @@

Training 

-2024-04-05 15:01:23,815 INFO cyclops.models.wrappers.sk_model - Best colsample_bytree: 0.7
+2024-04-08 09:18:04,780 INFO cyclops.models.wrappers.sk_model - Best colsample_bytree: 1
@@ -1618,26 +1618,26 @@

Training background-color: var(--sklearn-color-fitted-level-3); } 
XGBClassifier(base_score=None, booster=None, callbacks=None,
-              colsample_bylevel=None, colsample_bynode=None,
-              colsample_bytree=0.7, early_stopping_rounds=None,
-              enable_categorical=False, eval_metric='logloss',
-              feature_types=None, gamma=0, gpu_id=None, grow_policy=None,
-              importance_type=None, interaction_constraints=None,
-              learning_rate=0.1, max_bin=None, max_cat_threshold=None,
-              max_cat_to_onehot=None, max_delta_step=None, max_depth=5,
-              max_leaves=None, min_child_weight=3, missing=nan,
-              monotone_constraints=None, n_estimators=250, n_jobs=None,
-              num_parallel_tree=None, predictor=None, random_state=123, ...)
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.

+ colsample_bylevel=None, colsample_bynode=None, colsample_bytree=1, + early_stopping_rounds=None, enable_categorical=False, + eval_metric='logloss', feature_types=None, gamma=2, gpu_id=None, + grow_policy=None, importance_type=None, + interaction_constraints=None, learning_rate=0.1, max_bin=None, + max_cat_threshold=None, max_cat_to_onehot=None, + max_delta_step=None, max_depth=5, max_leaves=None, + min_child_weight=3, missing=nan, monotone_constraints=None, + n_estimators=250, n_jobs=None, num_parallel_tree=None, + predictor=None, random_state=123, ...)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org. 
[25]:
@@ -1653,7 +1653,7 @@ 
Training
 
-{'objective': 'binary:logistic', 'use_label_encoder': None, 'base_score': None, 'booster': None, 'callbacks': None, 'colsample_bylevel': None, 'colsample_bynode': None, 'colsample_bytree': 0.7, 'early_stopping_rounds': None, 'enable_categorical': False, 'eval_metric': 'logloss', 'feature_types': None, 'gamma': 0, 'gpu_id': None, 'grow_policy': None, 'importance_type': None, 'interaction_constraints': None, 'learning_rate': 0.1, 'max_bin': None, 'max_cat_threshold': None, 'max_cat_to_onehot': None, 'max_delta_step': None, 'max_depth': 5, 'max_leaves': None, 'min_child_weight': 3, 'missing': nan, 'monotone_constraints': None, 'n_estimators': 250, 'n_jobs': None, 'num_parallel_tree': None, 'predictor': None, 'random_state': 123, 'reg_alpha': None, 'reg_lambda': 0, 'sampling_method': None, 'scale_pos_weight': None, 'subsample': None, 'tree_method': None, 'validate_parameters': None, 'verbosity': None, 'seed': 123}
+{'objective': 'binary:logistic', 'use_label_encoder': None, 'base_score': None, 'booster': None, 'callbacks': None, 'colsample_bylevel': None, 'colsample_bynode': None, 'colsample_bytree': 1, 'early_stopping_rounds': None, 'enable_categorical': False, 'eval_metric': 'logloss', 'feature_types': None, 'gamma': 2, 'gpu_id': None, 'grow_policy': None, 'importance_type': None, 'interaction_constraints': None, 'learning_rate': 0.1, 'max_bin': None, 'max_cat_threshold': None, 'max_cat_to_onehot': None, 'max_delta_step': None, 'max_depth': 5, 'max_leaves': None, 'min_child_weight': 3, 'missing': nan, 'monotone_constraints': None, 'n_estimators': 250, 'n_jobs': None, 'num_parallel_tree': None, 'predictor': None, 'random_state': 123, 'reg_alpha': None, 'reg_lambda': 1, 'sampling_method': None, 'scale_pos_weight': None, 'subsample': None, 'tree_method': None, 'validate_parameters': None, 'verbosity': None, 'seed': 123}

Log the model parameters to the report.

@@ -1689,7 +1689,7 @@

Prediction

-
+
@@ -1814,91 +1814,91 @@

Evaluation

-
+
-
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Log the performance metrics to the report.

We can add a performance metric to the model card using the log_performance_metric method, which expects a dictionary where the keys are in the following format: slice_name/metric_name. For instance, overall/accuracy.

@@ -2024,9 +2024,9 @@

Evaluation
-

@@ -2525,5 +2525,7 @@

Report Generation + + \ No newline at end of file diff --git a/api/tutorials/mimiciv/mortality_prediction.ipynb b/api/tutorials/mimiciv/mortality_prediction.ipynb index b37d41d5d..d2b0e8e6a 100644 --- a/api/tutorials/mimiciv/mortality_prediction.ipynb +++ b/api/tutorials/mimiciv/mortality_prediction.ipynb @@ -21,10 +21,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2024-04-05T18:57:09.893257Z", - "iopub.status.busy": "2024-04-05T18:57:09.892434Z", - "iopub.status.idle": "2024-04-05T18:57:14.422185Z", - "shell.execute_reply": "2024-04-05T18:57:14.421373Z" + "iopub.execute_input": "2024-04-08T13:15:46.257801Z", + "iopub.status.busy": "2024-04-08T13:15:46.257156Z", + "iopub.status.idle": "2024-04-08T13:15:51.394332Z", + "shell.execute_reply": "2024-04-08T13:15:51.393523Z" } }, "outputs": [], @@ -89,10 +89,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2024-04-05T18:57:14.427752Z", - "iopub.status.busy": "2024-04-05T18:57:14.427165Z", - "iopub.status.idle": "2024-04-05T18:57:14.431365Z", - "shell.execute_reply": "2024-04-05T18:57:14.430750Z" + "iopub.execute_input": "2024-04-08T13:15:51.400431Z", + "iopub.status.busy": "2024-04-08T13:15:51.399843Z", + "iopub.status.idle": "2024-04-08T13:15:51.404250Z", + "shell.execute_reply": "2024-04-08T13:15:51.403588Z" } }, "outputs": [], @@ -112,10 +112,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2024-04-05T18:57:14.436543Z", - "iopub.status.busy": "2024-04-05T18:57:14.436195Z", - "iopub.status.idle": "2024-04-05T18:57:14.440156Z", - "shell.execute_reply": "2024-04-05T18:57:14.439453Z" + "iopub.execute_input": "2024-04-08T13:15:51.409576Z", + "iopub.status.busy": "2024-04-08T13:15:51.409188Z", + "iopub.status.idle": "2024-04-08T13:15:51.413824Z", + "shell.execute_reply": "2024-04-08T13:15:51.412839Z" } }, "outputs": [], @@ -147,10 +147,10 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2024-04-05T18:57:14.445680Z", - "iopub.status.busy": "2024-04-05T18:57:14.445266Z", - "iopub.status.idle": "2024-04-05T18:58:47.950035Z", - "shell.execute_reply": "2024-04-05T18:58:47.949311Z" + "iopub.execute_input": "2024-04-08T13:15:51.419470Z", + "iopub.status.busy": "2024-04-08T13:15:51.419016Z", + "iopub.status.idle": "2024-04-08T13:17:01.420617Z", + "shell.execute_reply": "2024-04-08T13:17:01.419486Z" } }, "outputs": [ @@ -158,21 +158,21 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-05 14:57:15,445 \u001b[1;37mINFO\u001b[0m cycquery.orm - Database setup, ready to run queries!\n" + "2024-04-08 09:15:53,763 \u001b[1;37mINFO\u001b[0m cycquery.orm - Database setup, ready to run queries!\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-05 14:57:22,990 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" + "2024-04-08 09:16:01,365 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-05 14:57:22,991 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 5.434670 s\n" + "2024-04-08 09:16:01,366 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 5.358807 s\n" ] }, { @@ -189,14 +189,14 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-05 14:57:53,105 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" + "2024-04-08 09:16:15,493 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-05 14:57:53,106 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 29.359461 s\n" + "2024-04-08 09:16:15,494 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 13.368719 s\n" ] }, { @@ -394,10 +394,10 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2024-04-05T18:58:47.955299Z", - "iopub.status.busy": "2024-04-05T18:58:47.954964Z", - "iopub.status.idle": "2024-04-05T18:58:48.102753Z", - "shell.execute_reply": "2024-04-05T18:58:48.101980Z" + "iopub.execute_input": "2024-04-08T13:17:01.426373Z", + "iopub.status.busy": "2024-04-08T13:17:01.425976Z", + "iopub.status.idle": "2024-04-08T13:17:01.570996Z", + "shell.execute_reply": "2024-04-08T13:17:01.570270Z" } }, "outputs": [ @@ -2395,9 +2395,9 @@ } }, "text/html": [ - "
+
@@ -1048,7 +1048,7 @@

Graphics

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@@ -1056,7 +1056,7 @@

Graphics

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@@ -1064,7 +1064,7 @@

Graphics

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@@ -1154,7 +1154,7 @@

Quantitative Analysis

- 0.9 + 0.72 @@ -1187,7 +1187,7 @@

Quantitative Analysis
- 0.21 + 0.15 @@ -1220,7 +1220,7 @@

Quantitative Analysis
- 0.27 + 0.03 @@ -1253,7 +1253,7 @@

Quantitative Analysis
- 0.2 + 0.52 @@ -1286,7 +1286,7 @@

Quantitative Analysis
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Quantitative Analysis
- 0.01 + 0.12 @@ -1351,7 +1351,7 @@

Graphics

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Graphics

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Graphics

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Graphics

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@@ -1485,7 +1485,7 @@

Version

- Date: 2024-04-05 + Date: 2024-04-08
@@ -1692,16 +1692,6 @@

Model Parameters

- - - - - - - - - - @@ -1715,7 +1705,7 @@

Model Parameters

Gamma

- 0 + 2
@@ -1732,10 +1722,6 @@

Gamma

-
-

Min_child_weight

- 3 -
@@ -1746,15 +1732,15 @@

Min_child_weight

-
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Missing

- nan -
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+

Objective

+ binary:logistic +
@@ -1765,15 +1751,15 @@

Missing

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+

Learning_rate

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N_estimators

- 250 -
@@ -1784,6 +1770,10 @@

N_estimators

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Min_child_weight

+ 3 +
@@ -1794,19 +1784,11 @@

N_estimators

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Reg_lambda

- 0 -
@@ -1827,6 +1809,10 @@

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@@ -1843,14 +1829,18 @@

Reg_lambda

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Enable_categorical

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Random_state

+ 123
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+

Eval_metric

+ logloss +
@@ -1861,14 +1851,18 @@

Enable_categorical

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+

Max_depth

+ 5 +
-

Objective

- binary:logistic +

Seed

+ 123
@@ -1880,10 +1874,6 @@

Objective

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Random_state

- 123 -
@@ -1905,8 +1895,8 @@

Random_state

-

Seed

- 123 +

Missing

+ nan
@@ -1918,6 +1908,15 @@

Seed

+
+

Reg_lambda

+ 1 +
+ + + + + @@ -1929,8 +1928,8 @@

Seed

-

Eval_metric

- logloss +

Enable_categorical

+ False
@@ -1944,17 +1943,18 @@

Eval_metric

Colsample_bytree

- 0.7 + 1
-
-

Max_depth

- 5 -
+ + + + + @@ -2278,9 +2278,9 @@

Ethical Considerations

} } var slices_all = JSON.parse("{\"0\": [\"metric:Accuracy\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"1\": [\"metric:Precision\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"2\": [\"metric:Recall\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"3\": [\"metric:F1 Score\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"4\": [\"metric:AUROC\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"5\": [\"metric:AveragePrecision\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"6\": [\"metric:Accuracy\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"7\": [\"metric:Precision\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"8\": [\"metric:Recall\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"9\": [\"metric:F1 Score\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"10\": [\"metric:AUROC\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"11\": [\"metric:AveragePrecision\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"12\": [\"metric:Accuracy\", \"gender:M\", \"age:overall_age\"], \"13\": [\"metric:Precision\", \"gender:M\", \"age:overall_age\"], \"14\": [\"metric:Recall\", \"gender:M\", \"age:overall_age\"], \"15\": [\"metric:F1 Score\", \"gender:M\", \"age:overall_age\"], \"16\": [\"metric:AUROC\", \"gender:M\", \"age:overall_age\"], \"17\": [\"metric:AveragePrecision\", \"gender:M\", \"age:overall_age\"], \"18\": [\"metric:Accuracy\", \"gender:F\", \"age:overall_age\"], \"19\": [\"metric:Precision\", \"gender:F\", \"age:overall_age\"], \"20\": [\"metric:Recall\", \"gender:F\", \"age:overall_age\"], \"21\": [\"metric:F1 Score\", \"gender:F\", \"age:overall_age\"], \"22\": [\"metric:AUROC\", \"gender:F\", \"age:overall_age\"], \"23\": [\"metric:AveragePrecision\", \"gender:F\", \"age:overall_age\"], \"24\": [\"metric:Accuracy\", \"age:overall_age\", \"gender:overall_gender\"], \"25\": [\"metric:Precision\", \"age:overall_age\", \"gender:overall_gender\"], \"26\": [\"metric:Recall\", \"age:overall_age\", \"gender:overall_gender\"], \"27\": [\"metric:F1 Score\", \"age:overall_age\", \"gender:overall_gender\"], \"28\": [\"metric:AUROC\", \"age:overall_age\", \"gender:overall_gender\"], \"29\": [\"metric:AveragePrecision\", \"age:overall_age\", \"gender:overall_gender\"]}"); 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+ var histories_all = JSON.parse("{\"0\": [\"0.9955686926841736\", \"1.0\", \"1.0\", \"0.9416535397648266\", \"1.0\"], \"1\": [\"1.0\", \"0.9358894976198078\", \"0.9381630649408353\", \"1.0\", \"1.0\"], \"2\": [\"0.25\", \"0.254509663180193\", \"0.4051246647121412\", \"0.40142714013156766\", \"0.2379678775190883\"], \"3\": [\"0.4000000059604645\", \"0.3974934970531119\", \"0.5655210497628401\", \"0.5600481510251835\", \"0.6022614865714296\"], \"4\": [\"0.8907875418663025\", \"0.8276804778373102\", \"0.8047717178766463\", \"0.7580271644526186\", \"0.7486304935047055\"], \"5\": [\"0.31141793727874756\", \"0.5484307719578945\", \"0.6678709731423097\", \"0.7291386034866677\", \"0.7943334814303428\"], \"6\": [\"0.974090039730072\", \"0.9344376938225075\", \"0.9751498919443231\", \"0.8663340243786378\", \"0.7713941844268117\"], \"7\": [\"0.21212121844291687\", \"0.2362801917705169\", \"0.2765128424780087\", \"0.23671038849035597\", \"0.09236212732674473\"], \"8\": [\"0.30434781312942505\", \"0.26363233226820676\", \"0.34892805009262395\", \"0.29717114796060967\", \"0.3185323694937827\"], \"9\": [\"0.25\", \"0.1993507798688167\", \"0.1925681567760767\", \"0.10405635396921296\", \"0.24008658549530576\"], \"10\": [\"0.8522610664367676\", \"0.8547489701146036\", \"0.6534973112936735\", \"0.7547069817683107\", \"0.9525821615186979\"], \"11\": [\"0.16923031210899353\", \"0.1708441593278247\", \"0.1932819952566045\", \"0.09170902722698016\", \"0.14110616643792445\"], \"12\": [\"0.9651162624359131\", \"1.0\", \"0.7241787204034659\", \"0.7853933216702249\", \"0.7119558833223476\"], \"13\": [\"0.25\", \"0.24881522741794163\", \"0.33847477175680096\", \"0.4994092998925164\", \"0.5615686892966744\"], \"14\": [\"0.25\", \"0.18512902714419324\", \"0.24908422806214164\", \"0.23556221080508988\", \"0.22238066097751705\"], \"15\": [\"0.25\", \"0.2060519003841019\", \"0.22603656426380508\", \"0.025452922726581062\", \"0.0\"], \"16\": [\"0.8507022261619568\", \"0.6621160811867901\", \"0.7090283822960545\", \"0.6484498786346591\", \"0.8474427949041227\"], \"17\": [\"0.19459454715251923\", \"0.03980043650811971\", \"0.15215672443405048\", \"0.05743084578064139\", \"0.0\"], \"18\": [\"0.9790115356445312\", \"0.9323861652598088\", \"0.8365006060056535\", \"0.6923042216974391\", \"0.7961076031616031\"], \"19\": [\"0.20000000298023224\", \"0.3743837858898009\", \"0.44627678038015417\", \"0.3386821082171572\", \"0.1851230870144918\"], \"20\": [\"0.21052631735801697\", \"0.18959829988065946\", \"0.39732732906191964\", \"0.2584508878677281\", \"0.22249778777817547\"], \"21\": [\"0.20512820780277252\", \"0.2415705919190837\", \"0.06722682118008516\", \"0.12394110464087828\", \"0.10896835507582045\"], \"22\": [\"0.8193992972373962\", \"0.9480037386023271\", \"0.9991211259833657\", \"0.899750614231608\", \"0.7887715835292974\"], \"23\": [\"0.11029169708490372\", \"0.09928503729239899\", \"0.12642329551591863\", \"0.09847993688141606\", \"0.0\"], \"24\": [\"0.9723098278045654\", \"0.8909504000301693\", \"0.8899047557789893\", \"0.742420323373001\", \"0.7208524115801279\"], \"25\": [\"0.23076923191547394\", \"0.14788442112428762\", \"0.05194466039825771\", \"0.048270217976368254\", \"0.15051862244841296\"], \"26\": [\"0.23529411852359772\", \"0.19808871034846248\", \"0.18617402649904588\", \"0.07550263652767499\", \"0.025760144794701838\"], \"27\": [\"0.2330097109079361\", \"0.45239616324429666\", \"0.46655206612454564\", \"0.6311144643196412\", \"0.5194824316188729\"], \"28\": [\"0.8422555923461914\", \"0.8605847128577409\", \"0.8461457697616539\", \"0.8637342583608214\", \"0.8439510616507098\"], \"29\": [\"0.153534933924675\", \"0.0408444666861289\", \"0.1581506212991156\", \"0.0\", \"0.12315437441078499\"]}"); var thresholds_all = JSON.parse("{\"0\": \"0.7\", \"1\": \"0.7\", \"2\": \"0.7\", \"3\": \"0.7\", \"4\": \"0.7\", \"5\": \"0.7\", \"6\": \"0.7\", \"7\": \"0.7\", \"8\": \"0.7\", \"9\": \"0.7\", \"10\": \"0.7\", \"11\": \"0.7\", \"12\": \"0.7\", \"13\": \"0.7\", \"14\": \"0.7\", \"15\": \"0.7\", \"16\": \"0.7\", \"17\": \"0.7\", \"18\": \"0.7\", \"19\": \"0.7\", \"20\": \"0.7\", \"21\": \"0.7\", \"22\": \"0.7\", \"23\": \"0.7\", \"24\": \"0.7\", \"25\": \"0.7\", \"26\": \"0.7\", \"27\": \"0.7\", \"28\": \"0.7\", \"29\": \"0.7\"}"); - var passed_all = JSON.parse("{\"0\": true, \"1\": false, \"2\": false, \"3\": false, \"4\": true, \"5\": false, \"6\": true, \"7\": false, \"8\": false, \"9\": false, \"10\": true, \"11\": false, \"12\": true, \"13\": false, \"14\": false, \"15\": false, \"16\": true, \"17\": false, \"18\": true, \"19\": false, \"20\": false, \"21\": false, \"22\": true, \"23\": false, \"24\": true, \"25\": false, \"26\": false, \"27\": false, \"28\": true, \"29\": false}"); + var passed_all = JSON.parse("{\"0\": true, \"1\": true, \"2\": false, \"3\": false, \"4\": true, \"5\": true, \"6\": true, \"7\": false, \"8\": false, \"9\": false, \"10\": true, \"11\": false, \"12\": true, \"13\": false, \"14\": false, \"15\": false, \"16\": true, \"17\": false, \"18\": true, \"19\": false, \"20\": false, \"21\": false, \"22\": true, \"23\": false, \"24\": true, \"25\": false, \"26\": false, \"27\": false, \"28\": true, \"29\": false}"); var names_all = JSON.parse("{\"0\": \"Accuracy\", \"1\": \"Precision\", \"2\": \"Recall\", \"3\": \"F1 Score\", \"4\": \"AUROC\", \"5\": \"AveragePrecision\", \"6\": \"Accuracy\", \"7\": \"Precision\", \"8\": \"Recall\", \"9\": \"F1 Score\", \"10\": \"AUROC\", \"11\": \"AveragePrecision\", \"12\": \"Accuracy\", \"13\": \"Precision\", \"14\": \"Recall\", \"15\": \"F1 Score\", \"16\": \"AUROC\", \"17\": \"AveragePrecision\", \"18\": \"Accuracy\", \"19\": \"Precision\", \"20\": \"Recall\", \"21\": \"F1 Score\", \"22\": \"AUROC\", \"23\": \"AveragePrecision\", \"24\": \"Accuracy\", \"25\": \"Precision\", \"26\": \"Recall\", \"27\": \"F1 Score\", \"28\": \"AUROC\", \"29\": \"AveragePrecision\"}"); var timestamps_all = JSON.parse("{\"0\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"1\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"2\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"3\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"4\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"5\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"6\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"7\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"8\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"9\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"10\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"11\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"12\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"13\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"14\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"15\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"16\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"17\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"18\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"19\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"20\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"21\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"22\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"23\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"24\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"25\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"26\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"27\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"28\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"29\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"]}"); @@ -2505,7 +2505,7 @@

Ethical Considerations

function generate_model_card_plot() { var model_card_plots = [] var overall_indices = [24, 25, 26, 27, 28, 29] - var histories = JSON.parse("{\"0\": [\"0.9940915703773499\", \"1.0\", \"1.0\", \"1.0\", \"0.9293217652862522\"], \"1\": [\"0.5\", \"0.6214600805556293\", \"0.5906869219791335\", \"0.6697007248894368\", \"0.5726746904793679\"], \"2\": [\"0.25\", \"0.30775944511457\", \"0.19949089928507702\", \"0.20045864856916312\", \"0.1472737388490708\"], \"3\": [\"0.3333333432674408\", \"0.21420763040627366\", \"0.16568780205023204\", \"0.11314183683522774\", \"0.0066285288357406935\"], \"4\": [\"0.8294947743415833\", \"0.9785515377017725\", \"0.8835015690945026\", \"0.8763648556268968\", \"0.8915973084766043\"], \"5\": [\"0.31436651945114136\", \"0.28093376553179294\", \"0.08309081137727095\", \"0.0\", \"0.0\"], \"6\": [\"0.9728562831878662\", \"0.7777458573694123\", \"0.9297759821650544\", \"0.890027860688909\", \"0.8018776814691426\"], \"7\": [\"0.1818181872367859\", \"0.18857312251007724\", \"0.21439072696430242\", \"0.3170134855290231\", \"0.44165933191937085\"], \"8\": [\"0.260869562625885\", \"0.2755254544176851\", \"0.20265771115024178\", \"0.07455537303269688\", \"0.07336579524222088\"], \"9\": [\"0.2142857164144516\", \"0.21082567478849412\", \"0.09006920876380824\", \"0.0\", \"0.0\"], \"10\": [\"0.8458127379417419\", \"0.8112762538889257\", \"0.9410821712056018\", \"0.8474559922109837\", \"0.9467847547126202\"], \"11\": [\"0.13276369869709015\", \"0.0\", \"0.0029766505101000724\", \"0.0\", \"0.07481408489651342\"], \"12\": [\"0.9643895626068115\", \"0.9596709393186982\", \"0.9273736532250805\", \"0.8328636098076072\", \"0.7397754828374709\"], \"13\": [\"0.22580644488334656\", \"0.2721159889239599\", \"0.21224951402346773\", \"0.11186962043915291\", \"0.0\"], \"14\": [\"0.21875\", \"0.1468546406609449\", \"0.23993191096122207\", \"0.13657662383151675\", \"0.15582894753905885\"], \"15\": [\"0.2222222238779068\", \"0.24455862376348728\", \"0.32070153544161895\", \"0.30194950801961556\", \"0.4502969658547009\"], \"16\": [\"0.8423548936843872\", \"0.8282000064598223\", \"0.8705258553861426\", \"0.8685166768332988\", \"0.9402068499865575\"], \"17\": [\"0.1919977366924286\", \"0.16071051932642239\", \"0.19016929398146026\", \"0.15512609782420927\", \"0.4153368977057972\"], \"18\": [\"0.9783344864845276\", \"0.9681963675410258\", \"1.0\", \"1.0\", \"1.0\"], \"19\": [\"0.190476194024086\", \"0.35044858410358326\", \"0.41603814315359483\", \"0.3406881679445502\", \"0.2982847037815797\"], \"20\": [\"0.21052631735801697\", \"0.28455106249173784\", \"0.4039430186599007\", \"0.36282476449905576\", \"0.23969918710878355\"], \"21\": [\"0.20000000298023224\", \"0.25130917168398575\", \"0.2350460379671442\", \"0.16004386842293408\", \"0.22941474726202954\"], \"22\": [\"0.7903761863708496\", \"0.6320680011911589\", \"0.7864311175641747\", \"0.8435241331733083\", \"0.9180822166187511\"], \"23\": [\"0.11608558148145676\", \"0.059525055987490826\", \"0.11185642692753966\", \"0.06317117604517651\", \"0.02919778303216359\"], \"24\": [\"0.9716088175773621\", \"0.9209151739284125\", \"0.7614859717008451\", \"0.7443703827318504\", \"0.8983414405937067\"], \"25\": [\"0.21153846383094788\", \"0.29288472064970317\", \"0.47047361916004815\", \"0.27369063617429135\", \"0.2083810481470011\"], \"26\": [\"0.21568627655506134\", \"0.275810466482585\", \"0.23987946895352236\", \"0.1753206123127934\", \"0.2680525414387135\"], \"27\": [\"0.21359223127365112\", \"0.20900128035349083\", \"0.1353738488015382\", \"0.03855684652419977\", \"0.1962953164143065\"], \"28\": [\"0.8256847262382507\", \"0.8112928021622988\", \"0.8876442659169705\", \"0.9789311943264116\", \"0.9948743291331094\"], \"29\": [\"0.1424722820520401\", \"0.04537688730146293\", \"0.03814866043913215\", \"0.003791285786322214\", \"0.009005267639049403\"]}"); + var histories = JSON.parse("{\"0\": [\"0.9955686926841736\", \"1.0\", \"1.0\", \"0.9416535397648266\", \"1.0\"], \"1\": [\"1.0\", \"0.9358894976198078\", \"0.9381630649408353\", \"1.0\", \"1.0\"], \"2\": [\"0.25\", \"0.254509663180193\", \"0.4051246647121412\", \"0.40142714013156766\", \"0.2379678775190883\"], \"3\": [\"0.4000000059604645\", \"0.3974934970531119\", \"0.5655210497628401\", \"0.5600481510251835\", \"0.6022614865714296\"], \"4\": [\"0.8907875418663025\", \"0.8276804778373102\", \"0.8047717178766463\", \"0.7580271644526186\", \"0.7486304935047055\"], \"5\": [\"0.31141793727874756\", \"0.5484307719578945\", \"0.6678709731423097\", \"0.7291386034866677\", \"0.7943334814303428\"], \"6\": [\"0.974090039730072\", \"0.9344376938225075\", \"0.9751498919443231\", \"0.8663340243786378\", \"0.7713941844268117\"], \"7\": [\"0.21212121844291687\", \"0.2362801917705169\", \"0.2765128424780087\", \"0.23671038849035597\", \"0.09236212732674473\"], \"8\": [\"0.30434781312942505\", \"0.26363233226820676\", \"0.34892805009262395\", \"0.29717114796060967\", \"0.3185323694937827\"], \"9\": [\"0.25\", \"0.1993507798688167\", \"0.1925681567760767\", \"0.10405635396921296\", \"0.24008658549530576\"], \"10\": [\"0.8522610664367676\", \"0.8547489701146036\", \"0.6534973112936735\", \"0.7547069817683107\", \"0.9525821615186979\"], \"11\": [\"0.16923031210899353\", \"0.1708441593278247\", \"0.1932819952566045\", \"0.09170902722698016\", \"0.14110616643792445\"], \"12\": [\"0.9651162624359131\", \"1.0\", \"0.7241787204034659\", \"0.7853933216702249\", \"0.7119558833223476\"], \"13\": [\"0.25\", \"0.24881522741794163\", \"0.33847477175680096\", \"0.4994092998925164\", \"0.5615686892966744\"], \"14\": [\"0.25\", \"0.18512902714419324\", \"0.24908422806214164\", \"0.23556221080508988\", \"0.22238066097751705\"], \"15\": [\"0.25\", \"0.2060519003841019\", \"0.22603656426380508\", \"0.025452922726581062\", \"0.0\"], \"16\": [\"0.8507022261619568\", \"0.6621160811867901\", \"0.7090283822960545\", \"0.6484498786346591\", \"0.8474427949041227\"], \"17\": [\"0.19459454715251923\", \"0.03980043650811971\", \"0.15215672443405048\", \"0.05743084578064139\", \"0.0\"], \"18\": [\"0.9790115356445312\", \"0.9323861652598088\", \"0.8365006060056535\", \"0.6923042216974391\", \"0.7961076031616031\"], \"19\": [\"0.20000000298023224\", \"0.3743837858898009\", \"0.44627678038015417\", \"0.3386821082171572\", \"0.1851230870144918\"], \"20\": [\"0.21052631735801697\", \"0.18959829988065946\", \"0.39732732906191964\", \"0.2584508878677281\", \"0.22249778777817547\"], \"21\": [\"0.20512820780277252\", \"0.2415705919190837\", \"0.06722682118008516\", \"0.12394110464087828\", \"0.10896835507582045\"], \"22\": [\"0.8193992972373962\", \"0.9480037386023271\", \"0.9991211259833657\", \"0.899750614231608\", \"0.7887715835292974\"], \"23\": [\"0.11029169708490372\", \"0.09928503729239899\", \"0.12642329551591863\", \"0.09847993688141606\", \"0.0\"], \"24\": [\"0.9723098278045654\", \"0.8909504000301693\", \"0.8899047557789893\", \"0.742420323373001\", \"0.7208524115801279\"], \"25\": [\"0.23076923191547394\", \"0.14788442112428762\", \"0.05194466039825771\", \"0.048270217976368254\", \"0.15051862244841296\"], \"26\": [\"0.23529411852359772\", \"0.19808871034846248\", \"0.18617402649904588\", \"0.07550263652767499\", \"0.025760144794701838\"], \"27\": [\"0.2330097109079361\", \"0.45239616324429666\", \"0.46655206612454564\", \"0.6311144643196412\", \"0.5194824316188729\"], \"28\": [\"0.8422555923461914\", \"0.8605847128577409\", \"0.8461457697616539\", \"0.8637342583608214\", \"0.8439510616507098\"], \"29\": [\"0.153534933924675\", \"0.0408444666861289\", \"0.1581506212991156\", \"0.0\", \"0.12315437441078499\"]}"); var thresholds = JSON.parse("{\"0\": \"0.7\", \"1\": \"0.7\", \"2\": \"0.7\", \"3\": \"0.7\", \"4\": \"0.7\", \"5\": \"0.7\", \"6\": \"0.7\", \"7\": \"0.7\", \"8\": \"0.7\", \"9\": \"0.7\", \"10\": \"0.7\", \"11\": \"0.7\", \"12\": \"0.7\", \"13\": \"0.7\", \"14\": \"0.7\", \"15\": \"0.7\", \"16\": \"0.7\", \"17\": \"0.7\", \"18\": \"0.7\", \"19\": \"0.7\", \"20\": \"0.7\", \"21\": \"0.7\", \"22\": \"0.7\", \"23\": \"0.7\", \"24\": \"0.7\", \"25\": \"0.7\", \"26\": \"0.7\", \"27\": \"0.7\", \"28\": \"0.7\", \"29\": \"0.7\"}"); var timestamps = JSON.parse("{\"0\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"1\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"2\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"3\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"4\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"5\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"6\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"7\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"8\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"9\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"10\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"11\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"12\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"13\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"14\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"15\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"16\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"17\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"18\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"19\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"20\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"21\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"22\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"23\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"24\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"25\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"26\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"27\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"28\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"29\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"]}"); @@ -2721,9 +2721,9 @@

Ethical Considerations

} } var slices_all = JSON.parse("{\"0\": [\"metric:Accuracy\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"1\": [\"metric:Precision\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"2\": [\"metric:Recall\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"3\": [\"metric:F1 Score\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"4\": [\"metric:AUROC\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"5\": [\"metric:AveragePrecision\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"6\": [\"metric:Accuracy\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"7\": [\"metric:Precision\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"8\": [\"metric:Recall\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"9\": [\"metric:F1 Score\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"10\": [\"metric:AUROC\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"11\": [\"metric:AveragePrecision\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"12\": [\"metric:Accuracy\", \"gender:M\", \"age:overall_age\"], \"13\": [\"metric:Precision\", \"gender:M\", \"age:overall_age\"], \"14\": [\"metric:Recall\", \"gender:M\", \"age:overall_age\"], \"15\": [\"metric:F1 Score\", \"gender:M\", \"age:overall_age\"], \"16\": [\"metric:AUROC\", \"gender:M\", \"age:overall_age\"], \"17\": [\"metric:AveragePrecision\", \"gender:M\", \"age:overall_age\"], \"18\": [\"metric:Accuracy\", \"gender:F\", \"age:overall_age\"], \"19\": [\"metric:Precision\", \"gender:F\", \"age:overall_age\"], \"20\": [\"metric:Recall\", \"gender:F\", \"age:overall_age\"], \"21\": [\"metric:F1 Score\", \"gender:F\", \"age:overall_age\"], \"22\": [\"metric:AUROC\", \"gender:F\", \"age:overall_age\"], \"23\": [\"metric:AveragePrecision\", \"gender:F\", \"age:overall_age\"], \"24\": [\"metric:Accuracy\", \"age:overall_age\", \"gender:overall_gender\"], \"25\": [\"metric:Precision\", \"age:overall_age\", \"gender:overall_gender\"], \"26\": [\"metric:Recall\", \"age:overall_age\", \"gender:overall_gender\"], \"27\": [\"metric:F1 Score\", \"age:overall_age\", \"gender:overall_gender\"], \"28\": [\"metric:AUROC\", \"age:overall_age\", \"gender:overall_gender\"], \"29\": [\"metric:AveragePrecision\", \"age:overall_age\", \"gender:overall_gender\"]}"); - var histories_all = JSON.parse("{\"0\": [\"0.9940915703773499\", \"1.0\", \"1.0\", \"1.0\", \"0.9293217652862522\"], \"1\": [\"0.5\", \"0.6214600805556293\", \"0.5906869219791335\", \"0.6697007248894368\", \"0.5726746904793679\"], \"2\": [\"0.25\", \"0.30775944511457\", \"0.19949089928507702\", \"0.20045864856916312\", \"0.1472737388490708\"], \"3\": [\"0.3333333432674408\", \"0.21420763040627366\", \"0.16568780205023204\", \"0.11314183683522774\", \"0.0066285288357406935\"], \"4\": [\"0.8294947743415833\", \"0.9785515377017725\", \"0.8835015690945026\", \"0.8763648556268968\", \"0.8915973084766043\"], \"5\": [\"0.31436651945114136\", \"0.28093376553179294\", \"0.08309081137727095\", \"0.0\", \"0.0\"], \"6\": [\"0.9728562831878662\", \"0.7777458573694123\", \"0.9297759821650544\", \"0.890027860688909\", \"0.8018776814691426\"], \"7\": [\"0.1818181872367859\", \"0.18857312251007724\", \"0.21439072696430242\", \"0.3170134855290231\", \"0.44165933191937085\"], \"8\": [\"0.260869562625885\", \"0.2755254544176851\", \"0.20265771115024178\", \"0.07455537303269688\", \"0.07336579524222088\"], \"9\": [\"0.2142857164144516\", \"0.21082567478849412\", \"0.09006920876380824\", \"0.0\", \"0.0\"], \"10\": [\"0.8458127379417419\", \"0.8112762538889257\", \"0.9410821712056018\", \"0.8474559922109837\", \"0.9467847547126202\"], \"11\": [\"0.13276369869709015\", \"0.0\", \"0.0029766505101000724\", \"0.0\", \"0.07481408489651342\"], \"12\": [\"0.9643895626068115\", \"0.9596709393186982\", \"0.9273736532250805\", \"0.8328636098076072\", \"0.7397754828374709\"], \"13\": [\"0.22580644488334656\", \"0.2721159889239599\", \"0.21224951402346773\", \"0.11186962043915291\", \"0.0\"], \"14\": [\"0.21875\", \"0.1468546406609449\", \"0.23993191096122207\", \"0.13657662383151675\", \"0.15582894753905885\"], \"15\": [\"0.2222222238779068\", \"0.24455862376348728\", \"0.32070153544161895\", \"0.30194950801961556\", \"0.4502969658547009\"], \"16\": [\"0.8423548936843872\", \"0.8282000064598223\", \"0.8705258553861426\", \"0.8685166768332988\", \"0.9402068499865575\"], \"17\": [\"0.1919977366924286\", \"0.16071051932642239\", \"0.19016929398146026\", \"0.15512609782420927\", \"0.4153368977057972\"], \"18\": [\"0.9783344864845276\", \"0.9681963675410258\", \"1.0\", \"1.0\", \"1.0\"], \"19\": [\"0.190476194024086\", \"0.35044858410358326\", \"0.41603814315359483\", \"0.3406881679445502\", \"0.2982847037815797\"], \"20\": [\"0.21052631735801697\", \"0.28455106249173784\", \"0.4039430186599007\", \"0.36282476449905576\", \"0.23969918710878355\"], \"21\": [\"0.20000000298023224\", \"0.25130917168398575\", \"0.2350460379671442\", \"0.16004386842293408\", \"0.22941474726202954\"], \"22\": [\"0.7903761863708496\", \"0.6320680011911589\", \"0.7864311175641747\", \"0.8435241331733083\", \"0.9180822166187511\"], \"23\": [\"0.11608558148145676\", \"0.059525055987490826\", \"0.11185642692753966\", \"0.06317117604517651\", \"0.02919778303216359\"], \"24\": [\"0.9716088175773621\", \"0.9209151739284125\", \"0.7614859717008451\", \"0.7443703827318504\", \"0.8983414405937067\"], \"25\": [\"0.21153846383094788\", \"0.29288472064970317\", \"0.47047361916004815\", \"0.27369063617429135\", \"0.2083810481470011\"], \"26\": [\"0.21568627655506134\", \"0.275810466482585\", \"0.23987946895352236\", \"0.1753206123127934\", \"0.2680525414387135\"], \"27\": [\"0.21359223127365112\", \"0.20900128035349083\", \"0.1353738488015382\", \"0.03855684652419977\", \"0.1962953164143065\"], \"28\": [\"0.8256847262382507\", \"0.8112928021622988\", \"0.8876442659169705\", \"0.9789311943264116\", \"0.9948743291331094\"], \"29\": [\"0.1424722820520401\", \"0.04537688730146293\", \"0.03814866043913215\", \"0.003791285786322214\", \"0.009005267639049403\"]}"); + var histories_all = JSON.parse("{\"0\": [\"0.9955686926841736\", \"1.0\", \"1.0\", \"0.9416535397648266\", \"1.0\"], \"1\": [\"1.0\", \"0.9358894976198078\", \"0.9381630649408353\", \"1.0\", \"1.0\"], \"2\": [\"0.25\", \"0.254509663180193\", \"0.4051246647121412\", \"0.40142714013156766\", \"0.2379678775190883\"], \"3\": [\"0.4000000059604645\", \"0.3974934970531119\", \"0.5655210497628401\", \"0.5600481510251835\", \"0.6022614865714296\"], \"4\": [\"0.8907875418663025\", \"0.8276804778373102\", \"0.8047717178766463\", \"0.7580271644526186\", \"0.7486304935047055\"], \"5\": [\"0.31141793727874756\", \"0.5484307719578945\", \"0.6678709731423097\", \"0.7291386034866677\", \"0.7943334814303428\"], \"6\": [\"0.974090039730072\", \"0.9344376938225075\", \"0.9751498919443231\", \"0.8663340243786378\", \"0.7713941844268117\"], \"7\": [\"0.21212121844291687\", \"0.2362801917705169\", \"0.2765128424780087\", \"0.23671038849035597\", \"0.09236212732674473\"], \"8\": [\"0.30434781312942505\", \"0.26363233226820676\", \"0.34892805009262395\", \"0.29717114796060967\", \"0.3185323694937827\"], \"9\": [\"0.25\", \"0.1993507798688167\", \"0.1925681567760767\", \"0.10405635396921296\", \"0.24008658549530576\"], \"10\": [\"0.8522610664367676\", \"0.8547489701146036\", \"0.6534973112936735\", \"0.7547069817683107\", \"0.9525821615186979\"], \"11\": [\"0.16923031210899353\", \"0.1708441593278247\", \"0.1932819952566045\", \"0.09170902722698016\", \"0.14110616643792445\"], \"12\": [\"0.9651162624359131\", \"1.0\", \"0.7241787204034659\", \"0.7853933216702249\", \"0.7119558833223476\"], \"13\": [\"0.25\", \"0.24881522741794163\", \"0.33847477175680096\", \"0.4994092998925164\", \"0.5615686892966744\"], \"14\": [\"0.25\", \"0.18512902714419324\", \"0.24908422806214164\", \"0.23556221080508988\", \"0.22238066097751705\"], \"15\": [\"0.25\", \"0.2060519003841019\", \"0.22603656426380508\", \"0.025452922726581062\", \"0.0\"], \"16\": [\"0.8507022261619568\", \"0.6621160811867901\", \"0.7090283822960545\", \"0.6484498786346591\", \"0.8474427949041227\"], \"17\": [\"0.19459454715251923\", \"0.03980043650811971\", \"0.15215672443405048\", \"0.05743084578064139\", \"0.0\"], \"18\": [\"0.9790115356445312\", \"0.9323861652598088\", \"0.8365006060056535\", \"0.6923042216974391\", \"0.7961076031616031\"], \"19\": [\"0.20000000298023224\", \"0.3743837858898009\", \"0.44627678038015417\", \"0.3386821082171572\", \"0.1851230870144918\"], \"20\": [\"0.21052631735801697\", \"0.18959829988065946\", \"0.39732732906191964\", \"0.2584508878677281\", \"0.22249778777817547\"], \"21\": [\"0.20512820780277252\", \"0.2415705919190837\", \"0.06722682118008516\", \"0.12394110464087828\", \"0.10896835507582045\"], \"22\": [\"0.8193992972373962\", \"0.9480037386023271\", \"0.9991211259833657\", \"0.899750614231608\", \"0.7887715835292974\"], \"23\": [\"0.11029169708490372\", \"0.09928503729239899\", \"0.12642329551591863\", \"0.09847993688141606\", \"0.0\"], \"24\": [\"0.9723098278045654\", \"0.8909504000301693\", \"0.8899047557789893\", \"0.742420323373001\", \"0.7208524115801279\"], \"25\": [\"0.23076923191547394\", \"0.14788442112428762\", \"0.05194466039825771\", \"0.048270217976368254\", \"0.15051862244841296\"], \"26\": [\"0.23529411852359772\", \"0.19808871034846248\", \"0.18617402649904588\", \"0.07550263652767499\", \"0.025760144794701838\"], \"27\": [\"0.2330097109079361\", \"0.45239616324429666\", \"0.46655206612454564\", \"0.6311144643196412\", \"0.5194824316188729\"], \"28\": [\"0.8422555923461914\", \"0.8605847128577409\", \"0.8461457697616539\", \"0.8637342583608214\", \"0.8439510616507098\"], \"29\": [\"0.153534933924675\", \"0.0408444666861289\", \"0.1581506212991156\", \"0.0\", \"0.12315437441078499\"]}"); var thresholds_all = JSON.parse("{\"0\": \"0.7\", \"1\": \"0.7\", \"2\": \"0.7\", \"3\": \"0.7\", \"4\": \"0.7\", \"5\": \"0.7\", \"6\": \"0.7\", \"7\": \"0.7\", \"8\": \"0.7\", \"9\": \"0.7\", \"10\": \"0.7\", \"11\": \"0.7\", \"12\": \"0.7\", \"13\": \"0.7\", \"14\": \"0.7\", \"15\": \"0.7\", \"16\": \"0.7\", \"17\": \"0.7\", \"18\": \"0.7\", \"19\": \"0.7\", \"20\": \"0.7\", \"21\": \"0.7\", \"22\": \"0.7\", \"23\": \"0.7\", \"24\": \"0.7\", \"25\": \"0.7\", \"26\": \"0.7\", \"27\": \"0.7\", \"28\": \"0.7\", \"29\": \"0.7\"}"); - var passed_all = JSON.parse("{\"0\": true, \"1\": false, \"2\": false, \"3\": false, \"4\": true, \"5\": false, \"6\": true, \"7\": false, \"8\": false, \"9\": false, \"10\": true, \"11\": false, \"12\": true, \"13\": false, \"14\": false, \"15\": false, \"16\": true, \"17\": false, \"18\": true, \"19\": false, \"20\": false, \"21\": false, \"22\": true, \"23\": false, \"24\": true, \"25\": false, \"26\": false, \"27\": false, \"28\": true, \"29\": false}"); + var passed_all = JSON.parse("{\"0\": true, \"1\": true, \"2\": false, \"3\": false, \"4\": true, \"5\": true, \"6\": true, \"7\": false, \"8\": false, \"9\": false, \"10\": true, \"11\": false, \"12\": true, \"13\": false, \"14\": false, \"15\": false, \"16\": true, \"17\": false, \"18\": true, \"19\": false, \"20\": false, \"21\": false, \"22\": true, \"23\": false, \"24\": true, \"25\": false, \"26\": false, \"27\": false, \"28\": true, \"29\": false}"); var names_all = JSON.parse("{\"0\": \"Accuracy\", \"1\": \"Precision\", \"2\": \"Recall\", \"3\": \"F1 Score\", \"4\": \"AUROC\", \"5\": \"AveragePrecision\", \"6\": \"Accuracy\", \"7\": \"Precision\", \"8\": \"Recall\", \"9\": \"F1 Score\", \"10\": \"AUROC\", \"11\": \"AveragePrecision\", \"12\": \"Accuracy\", \"13\": \"Precision\", \"14\": \"Recall\", \"15\": \"F1 Score\", \"16\": \"AUROC\", \"17\": \"AveragePrecision\", \"18\": \"Accuracy\", \"19\": \"Precision\", \"20\": \"Recall\", \"21\": \"F1 Score\", \"22\": \"AUROC\", \"23\": \"AveragePrecision\", \"24\": \"Accuracy\", \"25\": \"Precision\", \"26\": \"Recall\", \"27\": \"F1 Score\", \"28\": \"AUROC\", \"29\": \"AveragePrecision\"}"); var timestamps_all = JSON.parse("{\"0\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"1\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"2\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"3\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"4\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"5\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"6\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"7\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"8\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"9\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"10\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"11\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"12\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"13\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"14\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"15\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"16\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"17\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"18\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"19\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"20\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"21\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"22\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"23\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"24\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"25\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"26\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"27\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"28\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"29\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"]}"); @@ -3122,7 +3122,7 @@

Ethical Considerations

]; // create global variable for max_n_evals - var histories = JSON.parse("{\"0\": [\"0.9940915703773499\", \"1.0\", \"1.0\", \"1.0\", \"0.9293217652862522\"], \"1\": [\"0.5\", \"0.6214600805556293\", \"0.5906869219791335\", \"0.6697007248894368\", \"0.5726746904793679\"], \"2\": [\"0.25\", \"0.30775944511457\", \"0.19949089928507702\", \"0.20045864856916312\", \"0.1472737388490708\"], \"3\": [\"0.3333333432674408\", \"0.21420763040627366\", \"0.16568780205023204\", \"0.11314183683522774\", \"0.0066285288357406935\"], \"4\": [\"0.8294947743415833\", \"0.9785515377017725\", \"0.8835015690945026\", \"0.8763648556268968\", \"0.8915973084766043\"], \"5\": [\"0.31436651945114136\", \"0.28093376553179294\", \"0.08309081137727095\", \"0.0\", \"0.0\"], \"6\": [\"0.9728562831878662\", \"0.7777458573694123\", \"0.9297759821650544\", \"0.890027860688909\", \"0.8018776814691426\"], \"7\": [\"0.1818181872367859\", \"0.18857312251007724\", \"0.21439072696430242\", \"0.3170134855290231\", \"0.44165933191937085\"], \"8\": [\"0.260869562625885\", \"0.2755254544176851\", \"0.20265771115024178\", \"0.07455537303269688\", \"0.07336579524222088\"], \"9\": [\"0.2142857164144516\", \"0.21082567478849412\", \"0.09006920876380824\", \"0.0\", \"0.0\"], \"10\": [\"0.8458127379417419\", \"0.8112762538889257\", \"0.9410821712056018\", \"0.8474559922109837\", \"0.9467847547126202\"], \"11\": [\"0.13276369869709015\", \"0.0\", \"0.0029766505101000724\", \"0.0\", \"0.07481408489651342\"], \"12\": [\"0.9643895626068115\", \"0.9596709393186982\", \"0.9273736532250805\", \"0.8328636098076072\", \"0.7397754828374709\"], \"13\": [\"0.22580644488334656\", \"0.2721159889239599\", \"0.21224951402346773\", \"0.11186962043915291\", \"0.0\"], \"14\": [\"0.21875\", \"0.1468546406609449\", \"0.23993191096122207\", \"0.13657662383151675\", \"0.15582894753905885\"], \"15\": [\"0.2222222238779068\", \"0.24455862376348728\", \"0.32070153544161895\", \"0.30194950801961556\", \"0.4502969658547009\"], \"16\": [\"0.8423548936843872\", \"0.8282000064598223\", \"0.8705258553861426\", \"0.8685166768332988\", \"0.9402068499865575\"], \"17\": [\"0.1919977366924286\", \"0.16071051932642239\", \"0.19016929398146026\", \"0.15512609782420927\", \"0.4153368977057972\"], \"18\": [\"0.9783344864845276\", \"0.9681963675410258\", \"1.0\", \"1.0\", \"1.0\"], \"19\": [\"0.190476194024086\", \"0.35044858410358326\", \"0.41603814315359483\", \"0.3406881679445502\", \"0.2982847037815797\"], \"20\": [\"0.21052631735801697\", \"0.28455106249173784\", \"0.4039430186599007\", \"0.36282476449905576\", \"0.23969918710878355\"], \"21\": [\"0.20000000298023224\", \"0.25130917168398575\", \"0.2350460379671442\", \"0.16004386842293408\", \"0.22941474726202954\"], \"22\": [\"0.7903761863708496\", \"0.6320680011911589\", \"0.7864311175641747\", \"0.8435241331733083\", \"0.9180822166187511\"], \"23\": [\"0.11608558148145676\", \"0.059525055987490826\", \"0.11185642692753966\", \"0.06317117604517651\", \"0.02919778303216359\"], \"24\": [\"0.9716088175773621\", \"0.9209151739284125\", \"0.7614859717008451\", \"0.7443703827318504\", \"0.8983414405937067\"], \"25\": [\"0.21153846383094788\", \"0.29288472064970317\", \"0.47047361916004815\", \"0.27369063617429135\", \"0.2083810481470011\"], \"26\": [\"0.21568627655506134\", \"0.275810466482585\", \"0.23987946895352236\", \"0.1753206123127934\", \"0.2680525414387135\"], \"27\": [\"0.21359223127365112\", \"0.20900128035349083\", \"0.1353738488015382\", \"0.03855684652419977\", \"0.1962953164143065\"], \"28\": [\"0.8256847262382507\", \"0.8112928021622988\", \"0.8876442659169705\", \"0.9789311943264116\", \"0.9948743291331094\"], \"29\": [\"0.1424722820520401\", \"0.04537688730146293\", \"0.03814866043913215\", \"0.003791285786322214\", \"0.009005267639049403\"]}"); + var histories = JSON.parse("{\"0\": [\"0.9955686926841736\", \"1.0\", \"1.0\", \"0.9416535397648266\", \"1.0\"], \"1\": [\"1.0\", \"0.9358894976198078\", \"0.9381630649408353\", \"1.0\", \"1.0\"], \"2\": [\"0.25\", \"0.254509663180193\", \"0.4051246647121412\", \"0.40142714013156766\", \"0.2379678775190883\"], \"3\": [\"0.4000000059604645\", \"0.3974934970531119\", \"0.5655210497628401\", \"0.5600481510251835\", \"0.6022614865714296\"], \"4\": [\"0.8907875418663025\", \"0.8276804778373102\", \"0.8047717178766463\", \"0.7580271644526186\", \"0.7486304935047055\"], \"5\": [\"0.31141793727874756\", \"0.5484307719578945\", \"0.6678709731423097\", \"0.7291386034866677\", \"0.7943334814303428\"], \"6\": [\"0.974090039730072\", \"0.9344376938225075\", \"0.9751498919443231\", \"0.8663340243786378\", \"0.7713941844268117\"], \"7\": [\"0.21212121844291687\", \"0.2362801917705169\", \"0.2765128424780087\", \"0.23671038849035597\", \"0.09236212732674473\"], \"8\": [\"0.30434781312942505\", \"0.26363233226820676\", \"0.34892805009262395\", \"0.29717114796060967\", \"0.3185323694937827\"], \"9\": [\"0.25\", \"0.1993507798688167\", \"0.1925681567760767\", \"0.10405635396921296\", \"0.24008658549530576\"], \"10\": [\"0.8522610664367676\", \"0.8547489701146036\", \"0.6534973112936735\", \"0.7547069817683107\", \"0.9525821615186979\"], \"11\": [\"0.16923031210899353\", \"0.1708441593278247\", \"0.1932819952566045\", \"0.09170902722698016\", \"0.14110616643792445\"], \"12\": [\"0.9651162624359131\", \"1.0\", \"0.7241787204034659\", \"0.7853933216702249\", \"0.7119558833223476\"], \"13\": [\"0.25\", \"0.24881522741794163\", \"0.33847477175680096\", \"0.4994092998925164\", \"0.5615686892966744\"], \"14\": [\"0.25\", \"0.18512902714419324\", \"0.24908422806214164\", \"0.23556221080508988\", \"0.22238066097751705\"], \"15\": [\"0.25\", \"0.2060519003841019\", \"0.22603656426380508\", \"0.025452922726581062\", \"0.0\"], \"16\": [\"0.8507022261619568\", \"0.6621160811867901\", \"0.7090283822960545\", \"0.6484498786346591\", \"0.8474427949041227\"], \"17\": [\"0.19459454715251923\", \"0.03980043650811971\", \"0.15215672443405048\", \"0.05743084578064139\", \"0.0\"], \"18\": [\"0.9790115356445312\", \"0.9323861652598088\", \"0.8365006060056535\", \"0.6923042216974391\", \"0.7961076031616031\"], \"19\": [\"0.20000000298023224\", \"0.3743837858898009\", \"0.44627678038015417\", \"0.3386821082171572\", \"0.1851230870144918\"], \"20\": [\"0.21052631735801697\", \"0.18959829988065946\", \"0.39732732906191964\", \"0.2584508878677281\", \"0.22249778777817547\"], \"21\": [\"0.20512820780277252\", \"0.2415705919190837\", \"0.06722682118008516\", \"0.12394110464087828\", \"0.10896835507582045\"], \"22\": [\"0.8193992972373962\", \"0.9480037386023271\", \"0.9991211259833657\", \"0.899750614231608\", \"0.7887715835292974\"], \"23\": [\"0.11029169708490372\", \"0.09928503729239899\", \"0.12642329551591863\", \"0.09847993688141606\", \"0.0\"], \"24\": [\"0.9723098278045654\", \"0.8909504000301693\", \"0.8899047557789893\", \"0.742420323373001\", \"0.7208524115801279\"], \"25\": [\"0.23076923191547394\", \"0.14788442112428762\", \"0.05194466039825771\", \"0.048270217976368254\", \"0.15051862244841296\"], \"26\": [\"0.23529411852359772\", \"0.19808871034846248\", \"0.18617402649904588\", \"0.07550263652767499\", \"0.025760144794701838\"], \"27\": [\"0.2330097109079361\", \"0.45239616324429666\", \"0.46655206612454564\", \"0.6311144643196412\", \"0.5194824316188729\"], \"28\": [\"0.8422555923461914\", \"0.8605847128577409\", \"0.8461457697616539\", \"0.8637342583608214\", \"0.8439510616507098\"], \"29\": [\"0.153534933924675\", \"0.0408444666861289\", \"0.1581506212991156\", \"0.0\", \"0.12315437441078499\"]}"); // get max_n_evals from histories var history_data = []; for (let i = 0; i < histories[0].length; i++) { diff --git a/api/tutorials/nihcxr/cxr_classification.html b/api/tutorials/nihcxr/cxr_classification.html index faa356e61..271f0eb9d 100644 --- a/api/tutorials/nihcxr/cxr_classification.html +++ b/api/tutorials/nihcxr/cxr_classification.html @@ -431,13 +431,13 @@

Model Creation

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+
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Multilabel AUROC by Pathology and Sex

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@@ -581,61 +581,61 @@

Multilabel AUROC by Pathology and Age
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[8]:
@@ -689,9 +689,9 @@ 
Multilabel AUROC by Pathology and Age
-

@@ -1127,5 +1127,7 @@

Populate Model Card Fields + + \ No newline at end of file diff --git a/api/tutorials/nihcxr/cxr_classification.ipynb b/api/tutorials/nihcxr/cxr_classification.ipynb index dd76d464d..79365483b 100644 --- a/api/tutorials/nihcxr/cxr_classification.ipynb +++ b/api/tutorials/nihcxr/cxr_classification.ipynb @@ -24,10 +24,10 @@ "id": "fc1eb72a", "metadata": { "execution": { - "iopub.execute_input": "2024-04-05T19:01:38.755773Z", - "iopub.status.busy": "2024-04-05T19:01:38.755237Z", - "iopub.status.idle": "2024-04-05T19:01:45.324636Z", - "shell.execute_reply": "2024-04-05T19:01:45.323816Z" + "iopub.execute_input": "2024-04-08T13:18:18.909344Z", + "iopub.status.busy": "2024-04-08T13:18:18.908683Z", + "iopub.status.idle": "2024-04-08T13:18:24.409115Z", + "shell.execute_reply": "2024-04-08T13:18:24.408255Z" } }, "outputs": [], @@ -69,10 +69,10 @@ "id": "25c2a16f", "metadata": { "execution": { - "iopub.execute_input": "2024-04-05T19:01:45.330587Z", - "iopub.status.busy": "2024-04-05T19:01:45.330211Z", - "iopub.status.idle": "2024-04-05T19:07:07.691672Z", - "shell.execute_reply": "2024-04-05T19:07:07.689679Z" + "iopub.execute_input": "2024-04-08T13:18:24.414935Z", + "iopub.status.busy": "2024-04-08T13:18:24.414422Z", + "iopub.status.idle": "2024-04-08T13:23:49.290567Z", + "shell.execute_reply": "2024-04-08T13:23:49.288218Z" }, "nbsphinx": "hidden" }, @@ -90,14 +90,28 @@ "output_type": "stream", "text": [ "\r", - "Flattening the indices: 100%|████████| 1000/1000 [00:54<00:00, 18.51 examples/s]\r", - "Flattening the indices: 100%|████████| 1000/1000 [00:54<00:00, 18.50 examples/s]\r\n", + "Flattening the indices: 100%|████████| 1000/1000 [00:55<00:00, 17.94 examples/s]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "\r", - "Flattening the indices: 0%| | 0/1000 [00:00 Patient Gender:M: 0%| | 0/400 [00:00 Patient Gender:M: 100%|███| 400/400 [00:00<00:00, 43311.69 examples/s]\r\n" + "Filter -> Patient Gender:M: 100%|███| 400/400 [00:00<00:00, 18084.74 examples/s]\r\n" ] }, { @@ -120,7 +141,7 @@ "text": [ "\r", "Filter -> Patient Gender:F: 0%| | 0/400 [00:00 Patient Gender:F: 100%|███| 400/400 [00:00<00:00, 43503.74 examples/s]\r\n", + "Filter -> Patient Gender:F: 100%|███| 400/400 [00:00<00:00, 43255.86 examples/s]\r\n", "\r", "Filter -> overall: 0%| | 0/400 [00:00 overall: 100%|████████████| 400/400 [00:00<00:00, 45052.81 examples/s]\r\n", + "Filter -> overall: 100%|████████████| 400/400 [00:00<00:00, 45125.52 examples/s]\r\n", "\r", "Filter -> Patient Age:[19 - 35]: 0%| | 0/400 [00:00 Patient Age:[19 - 35]: 100%|█| 400/400 [00:00<00:00, 41490.79 examples\r\n", + "Filter -> Patient Age:[19 - 35]: 100%|█| 400/400 [00:00<00:00, 41043.17 examples\r\n", "\r", "Filter -> Patient Age:[35 - 65]: 0%| | 0/400 [00:00 Patient Age:[35 - 65]: 100%|█| 400/400 [00:00<00:00, 42661.89 examples\r\n", + "Filter -> Patient Age:[35 - 65]: 100%|█| 400/400 [00:00<00:00, 42646.71 examples\r\n", "\r", "Filter -> Patient Age:[65 - 100]: 0%| | 0/400 [00:00 Patient Age:[65 - 100]: 100%|█| 400/400 [00:00<00:00, 41631.84 example\r\n", + "Filter -> Patient Age:[65 - 100]: 100%|█| 400/400 [00:00<00:00, 41592.62 example\r\n", "\r", "Filter -> Patient Age:[19 - 35]&Patient Gender:M: 0%| | 0/400 [00:00 Patient Age:[19 - 35]&Patient Gender:M: 100%|█| 400/400 [00:00<00:00, \r\n", @@ -186,7 +207,7 @@ "Filter -> Patient Age:[65 - 100]&Patient Gender:F: 100%|█| 400/400 [00:00<00:00,\r\n", "\r", "Filter -> overall: 0%| | 0/400 [00:00 overall: 100%|████████████| 400/400 [00:00<00:00, 46988.42 examples/s]\r\n" + "Filter -> overall: 100%|████████████| 400/400 [00:00<00:00, 47915.74 examples/s]\r\n" ] }, { @@ -202,7 +223,7 @@ "output_type": "stream", "text": [ "\r", - "Flattening the indices: 100%|████████| 1000/1000 [00:53<00:00, 18.83 examples/s]" + "Flattening the indices: 100%|████████| 1000/1000 [00:53<00:00, 18.76 examples/s]" ] }, { @@ -210,13 +231,13 @@ "output_type": "stream", "text": [ "\r", - "Flattening the indices: 100%|████████| 1000/1000 [00:53<00:00, 18.83 examples/s]\r\n", + "Flattening the indices: 100%|████████| 1000/1000 [00:53<00:00, 18.75 examples/s]\r\n", "\r", "Flattening the indices: 0%| | 0/1000 [00:00 Patient Gender:M: 0%| | 0/396 [00:00 Patient Gender:M: 100%|███| 396/396 [00:00<00:00, 41514.27 examples/s]\r\n", + "Filter -> Patient Gender:M: 100%|███| 396/396 [00:00<00:00, 42065.20 examples/s]\r\n", "\r", "Filter -> Patient Gender:F: 0%| | 0/396 [00:00 Patient Gender:F: 100%|███| 396/396 [00:00<00:00, 41869.03 examples/s]\r\n" + "Filter -> Patient Gender:F: 100%|███| 396/396 [00:00<00:00, 42465.28 examples/s]\r\n" ] }, { @@ -249,7 +270,7 @@ "text": [ "\r", "Filter -> overall: 0%| | 0/396 [00:00 overall: 100%|████████████| 396/396 [00:00<00:00, 46523.75 examples/s]\r\n" + "Filter -> overall: 100%|████████████| 396/396 [00:00<00:00, 44716.36 examples/s]\r\n" ] }, { @@ -258,10 +279,10 @@ "text": [ "\r", "Filter -> Patient Age:[19 - 35]: 0%| | 0/396 [00:00 Patient Age:[19 - 35]: 100%|█| 396/396 [00:00<00:00, 41243.16 examples\r\n", + "Filter -> Patient Age:[19 - 35]: 100%|█| 396/396 [00:00<00:00, 40963.43 examples\r\n", "\r", "Filter -> Patient Age:[35 - 65]: 0%| | 0/396 [00:00 Patient Age:[35 - 65]: 100%|█| 396/396 [00:00<00:00, 43713.66 examples\r\n" + "Filter -> Patient Age:[35 - 65]: 100%|█| 396/396 [00:00<00:00, 42479.40 examples\r\n" ] }, { @@ -270,7 +291,7 @@ "text": [ "\r", "Filter -> Patient Age:[65 - 100]: 0%| | 0/396 [00:00 Patient Age:[65 - 100]: 100%|█| 396/396 [00:00<00:00, 43203.13 example\r\n", + "Filter -> Patient Age:[65 - 100]: 100%|█| 396/396 [00:00<00:00, 40964.44 example\r\n", "\r", "Filter -> Patient Age:[19 - 35]&Patient Gender:M: 0%| | 0/396 [00:00 Patient Age:[19 - 35]&Patient Gender:M: 100%|█| 396/396 [00:00<00:00, \r\n", @@ -288,21 +309,22 @@ "Filter -> Patient Age:[35 - 65]&Patient Gender:M: 0%| | 0/396 [00:00 Patient Age:[35 - 65]&Patient Gender:M: 100%|█| 396/396 [00:00<00:00, \r\n", "\r", - "Filter -> Patient Age:[35 - 65]&Patient Gender:F: 0%| | 0/396 [00:00 Patient Age:[35 - 65]&Patient Gender:F: 0%| | 0/396 [00:00 Patient Age:[35 - 65]&Patient Gender:F: 100%|█| 396/396 [00:00<00:00, \r\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "\r", - "Filter -> Patient Age:[35 - 65]&Patient Gender:F: 100%|█| 396/396 [00:00<00:00, \r\n", "\r", "Filter -> Patient Age:[65 - 100]&Patient Gender:M: 0%| | 0/396 [00:00 Patient Age:[65 - 100]&Patient Gender:M: 100%|█| 396/396 [00:00<00:00,\r\n", "\r", "Filter -> Patient Age:[65 - 100]&Patient Gender:F: 0%| | 0/396 [00:00 Patient Age:[65 - 100]&Patient Gender:F: 100%|█| 396/396 [00:00<00:00,\r\n" + "Filter -> Patient Age:[65 - 100]&Patient Gender:F: 100%|█| 396/396 [00:00<00:00,\r\n", + "\r", + "Filter -> overall: 0%| | 0/396 [00:00 overall: 0%| | 0/396 [00:00 overall: 100%|████████████| 396/396 [00:00<00:00, 46267.15 examples/s]\r\n" + "Filter -> overall: 100%|████████████| 396/396 [00:00<00:00, 46211.80 examples/s]\r\n" ] }, { @@ -327,14 +348,21 @@ "output_type": "stream", "text": [ "\r", - "Flattening the indices: 100%|████████| 1000/1000 [00:53<00:00, 18.73 examples/s]\r", - "Flattening the indices: 100%|████████| 1000/1000 [00:53<00:00, 18.72 examples/s]\r\n", + "Flattening the indices: 100%|████████| 1000/1000 [00:53<00:00, 18.64 examples/s]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\r", + "Flattening the indices: 100%|████████| 1000/1000 [00:53<00:00, 18.63 examples/s]\r\n", "\r", "Flattening the indices: 0%| | 0/1000 [00:00 Patient Gender:M: 0%| | 0/383 [00:00 Patient Gender:M: 100%|███| 383/383 [00:00<00:00, 42187.57 examples/s]\r\n" + "Filter -> Patient Gender:M: 0%| | 0/383 [00:00 Patient Gender:M: 100%|███| 383/383 [00:00<00:00, 42290.86 examples/s]\r\n", "\r", "Filter -> Patient Gender:F: 0%| | 0/383 [00:00 Patient Gender:F: 100%|███| 383/383 [00:00<00:00, 42422.65 examples/s]\r\n", + "Filter -> Patient Gender:F: 100%|███| 383/383 [00:00<00:00, 42965.00 examples/s]\r\n", "\r", - "Filter -> overall: 0%| | 0/383 [00:00 overall: 100%|████████████| 383/383 [00:00<00:00, 45168.52 examples/s]\r\n" + "Filter -> overall: 0%| | 0/383 [00:00 Patient Age:[19 - 35]: 0%| | 0/383 [00:00 Patient Age:[19 - 35]: 100%|█| 383/383 [00:00<00:00, 40992.61 examples\r\n" + "Filter -> overall: 100%|████████████| 383/383 [00:00<00:00, 44204.02 examples/s]\r\n", + "\r", + "Filter -> Patient Age:[19 - 35]: 0%| | 0/383 [00:00 Patient Age:[19 - 35]: 100%|█| 383/383 [00:00<00:00, 39932.84 examples\r\n", "\r", "Filter -> Patient Age:[35 - 65]: 0%| | 0/383 [00:00 Patient Age:[35 - 65]: 100%|█| 383/383 [00:00<00:00, 41859.98 examples\r\n", + "Filter -> Patient Age:[35 - 65]: 100%|█| 383/383 [00:00<00:00, 42225.28 examples\r\n", "\r", - "Filter -> Patient Age:[65 - 100]: 0%| | 0/383 [00:00 Patient Age:[65 - 100]: 100%|█| 383/383 [00:00<00:00, 41030.30 example\r\n" + "Filter -> Patient Age:[65 - 100]: 0%| | 0/383 [00:00 Patient Age:[65 - 100]: 100%|█| 383/383 [00:00<00:00, 41088.02 example\r\n", "\r", "Filter -> Patient Age:[19 - 35]&Patient Gender:M: 0%| | 0/383 [00:00 Patient Age:[19 - 35]&Patient Gender:M: 100%|█| 383/383 [00:00<00:00, \r\n", @@ -408,20 +440,21 @@ "Filter -> Patient Age:[35 - 65]&Patient Gender:F: 0%| | 0/383 [00:00 Patient Age:[35 - 65]&Patient Gender:F: 100%|█| 383/383 [00:00<00:00, \r\n", "\r", - "Filter -> Patient Age:[65 - 100]&Patient Gender:M: 0%| | 0/383 [00:00 Patient Age:[65 - 100]&Patient Gender:M: 100%|█| 383/383 [00:00<00:00,\r\n" + "Filter -> Patient Age:[65 - 100]&Patient Gender:M: 0%| | 0/383 [00:00 Patient Age:[65 - 100]&Patient Gender:M: 100%|█| 383/383 [00:00<00:00,\r\n", "\r", "Filter -> Patient Age:[65 - 100]&Patient Gender:F: 0%| | 0/383 [00:00 Patient Age:[65 - 100]&Patient Gender:F: 100%|█| 383/383 [00:00<00:00,\r\n", "\r", "Filter -> overall: 0%| | 0/383 [00:00 overall: 100%|████████████| 383/383 [00:00<00:00, 46281.14 examples/s]\r\n" + "Filter -> overall: 100%|████████████| 383/383 [00:00<00:00, 46168.08 examples/s]\r\n" ] }, { @@ -437,7 +470,7 @@ "output_type": "stream", "text": [ "\r", - "Flattening the indices: 100%|████████| 1000/1000 [00:52<00:00, 18.88 examples/s]" + "Flattening the indices: 100%|████████| 1000/1000 [00:53<00:00, 18.74 examples/s]" ] }, { @@ -445,13 +478,13 @@ "output_type": "stream", "text": [ "\r", - "Flattening the indices: 100%|████████| 1000/1000 [00:52<00:00, 18.87 examples/s]\r\n", + "Flattening the indices: 100%|████████| 1000/1000 [00:53<00:00, 18.74 examples/s]\r\n", "\r", "Flattening the indices: 0%| | 0/1000 [00:00 Patient Gender:M: 0%| | 0/411 [00:00 Patient Gender:M: 100%|███| 411/411 [00:00<00:00, 43982.73 examples/s]\r\n", + "Filter -> Patient Gender:M: 100%|███| 411/411 [00:00<00:00, 43107.25 examples/s]\r\n", "\r", - "Filter -> Patient Gender:F: 0%| | 0/411 [00:00 Patient Gender:F: 0%| | 0/411 [00:00 Patient Gender:F: 100%|███| 411/411 [00:00<00:00, 43651.94 examples/s]\r\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "\r", - "Filter -> Patient Gender:F: 100%|███| 411/411 [00:00<00:00, 43547.19 examples/s]\r\n", "\r", "Filter -> overall: 0%| | 0/411 [00:00 overall: 100%|████████████| 411/411 [00:00<00:00, 46006.38 examples/s]\r\n" + "Filter -> overall: 100%|████████████| 411/411 [00:00<00:00, 45996.56 examples/s]\r\n" ] }, { @@ -493,20 +525,19 @@ "text": [ "\r", "Filter -> Patient Age:[19 - 35]: 0%| | 0/411 [00:00 Patient Age:[19 - 35]: 100%|█| 411/411 [00:00<00:00, 42349.01 examples\r\n", + "Filter -> Patient Age:[19 - 35]: 100%|█| 411/411 [00:00<00:00, 41942.02 examples\r\n", "\r", - "Filter -> Patient Age:[35 - 65]: 0%| | 0/411 [00:00 Patient Age:[35 - 65]: 0%| | 0/411 [00:00 Patient Age:[35 - 65]: 100%|█| 411/411 [00:00<00:00, 42840.50 examples\r\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "\r", - "Filter -> Patient Age:[35 - 65]: 100%|█| 411/411 [00:00<00:00, 42095.65 examples\r\n", "\r", "Filter -> Patient Age:[65 - 100]: 0%| | 0/411 [00:00 Patient Age:[65 - 100]: 100%|█| 411/411 [00:00<00:00, 41032.54 example\r\n", + "Filter -> Patient Age:[65 - 100]: 100%|█| 411/411 [00:00<00:00, 42417.79 example\r\n", "\r", "Filter -> Patient Age:[19 - 35]&Patient Gender:M: 0%| | 0/411 [00:00 Patient Age:[35 - 65]&Patient Gender:F: 100%|█| 411/411 [00:00<00:00, \r\n", "\r", "Filter -> Patient Age:[65 - 100]&Patient Gender:M: 0%| | 0/411 [00:00 Patient Age:[65 - 100]&Patient Gender:M: 100%|█| 411/411 [00:00<00:00,\r\n" + "Filter -> Patient Age:[65 - 100]&Patient Gender:M: 100%|█| 411/411 [00:00<00:00,\r\n", + "\r", + "Filter -> Patient Age:[65 - 100]&Patient Gender:F: 0%| | 0/411 [00:00 Patient Age:[65 - 100]&Patient Gender:F: 0%| | 0/411 [00:00 Patient Age:[65 - 100]&Patient Gender:F: 100%|█| 411/411 [00:00<00:00,\r\n", "\r", "Filter -> overall: 0%| | 0/411 [00:00 overall: 100%|████████████| 411/411 [00:00<00:00, 47698.15 examples/s]\r\n" + "Filter -> overall: 100%|████████████| 411/411 [00:00<00:00, 47438.26 examples/s]\r\n" ] } ], @@ -594,10 +626,10 @@ "id": "03edf1c0", "metadata": { "execution": { - "iopub.execute_input": "2024-04-05T19:07:07.699109Z", - "iopub.status.busy": "2024-04-05T19:07:07.698388Z", - "iopub.status.idle": "2024-04-05T19:07:07.707996Z", - "shell.execute_reply": "2024-04-05T19:07:07.706113Z" + "iopub.execute_input": "2024-04-08T13:23:49.298786Z", + "iopub.status.busy": "2024-04-08T13:23:49.298157Z", + "iopub.status.idle": "2024-04-08T13:23:49.308143Z", + "shell.execute_reply": "2024-04-08T13:23:49.305842Z" } }, "outputs": [], @@ -619,10 +651,10 @@ "id": "6514120e", "metadata": { "execution": { - "iopub.execute_input": "2024-04-05T19:07:07.714061Z", - "iopub.status.busy": "2024-04-05T19:07:07.713543Z", - "iopub.status.idle": "2024-04-05T19:07:11.028408Z", - "shell.execute_reply": "2024-04-05T19:07:11.027477Z" + "iopub.execute_input": "2024-04-08T13:23:49.315271Z", + "iopub.status.busy": "2024-04-08T13:23:49.314400Z", + "iopub.status.idle": "2024-04-08T13:23:52.626532Z", + "shell.execute_reply": "2024-04-08T13:23:52.625239Z" } }, "outputs": [], @@ -666,17 +698,17 @@ "id": "5f624ed4", "metadata": { "execution": { - "iopub.execute_input": "2024-04-05T19:07:11.033637Z", - "iopub.status.busy": "2024-04-05T19:07:11.033285Z", - "iopub.status.idle": "2024-04-05T19:07:24.722649Z", - "shell.execute_reply": "2024-04-05T19:07:24.721956Z" + "iopub.execute_input": "2024-04-08T13:23:52.632153Z", + "iopub.status.busy": "2024-04-08T13:23:52.631822Z", + "iopub.status.idle": "2024-04-08T13:24:06.188170Z", + "shell.execute_reply": "2024-04-08T13:24:06.187486Z" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "54056d475c294798b05394a5a150622b", + "model_id": "1d283c16fdd04994a99ce0f9f9c9fc00", "version_major": 2, "version_minor": 0 }, @@ -690,7 +722,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "daac3789dc1146a4ab3bfab35e8c8c83", + "model_id": "7083d8c4664c4285bd8571f119ba12a4", "version_major": 2, "version_minor": 0 }, @@ -750,17 +782,17 @@ "id": "bff27cc1", "metadata": { "execution": { - "iopub.execute_input": "2024-04-05T19:07:24.731474Z", - "iopub.status.busy": "2024-04-05T19:07:24.731272Z", - "iopub.status.idle": "2024-04-05T19:07:24.969193Z", - "shell.execute_reply": "2024-04-05T19:07:24.968507Z" + "iopub.execute_input": "2024-04-08T13:24:06.196567Z", + "iopub.status.busy": "2024-04-08T13:24:06.196321Z", + "iopub.status.idle": "2024-04-08T13:24:06.414752Z", + "shell.execute_reply": "2024-04-08T13:24:06.413572Z" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "e6f9e24368e14af4a8d27de9cd2ff4ee", + "model_id": "4a13de2d264f4e8c89b301d440721804", "version_major": 2, "version_minor": 0 }, @@ -774,7 +806,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "f4bfc359e548453b861c56b4b0afe437", + "model_id": "8c6a0ebd9d254d95a99a92929eca3f35", "version_major": 2, "version_minor": 0 }, @@ -788,7 +820,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "8007361621f0457caded499aedafcb8a", + "model_id": "ccf6b6db38a04f918cca740aba1c8d99", "version_major": 2, "version_minor": 0 }, @@ -866,17 +898,17 @@ "id": "8c38ef9e", "metadata": { "execution": { - "iopub.execute_input": "2024-04-05T19:07:24.974211Z", - "iopub.status.busy": "2024-04-05T19:07:24.974005Z", - "iopub.status.idle": "2024-04-05T19:07:25.447321Z", - "shell.execute_reply": "2024-04-05T19:07:25.446154Z" + "iopub.execute_input": "2024-04-08T13:24:06.420070Z", + "iopub.status.busy": "2024-04-08T13:24:06.419746Z", + "iopub.status.idle": "2024-04-08T13:24:06.900956Z", + "shell.execute_reply": "2024-04-08T13:24:06.900048Z" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "b95d0631e1e74bc3a17bd038210aa08d", + "model_id": "5392adb754e641318dcd0b1c5b82da05", "version_major": 2, "version_minor": 0 }, @@ -890,7 +922,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "d20260e086b24b819ecd67c1fffb3ac3", + "model_id": "f521fb65d4f645f6bfa560dde6c7080d", "version_major": 2, "version_minor": 0 }, @@ -904,7 +936,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "6bfae75b90cf45b6b5c34c0b7a073151", + "model_id": "8fa69eb2ac0d4ec3bb26f17e3fc53bad", "version_major": 2, "version_minor": 0 }, @@ -918,7 +950,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "fc4bb55f9d3c4a3b9ce19649fda2d1cb", + "model_id": "85c7964dfc7e46f3807aedcd5ee2ef2c", "version_major": 2, "version_minor": 0 }, @@ -932,7 +964,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "76d64a03102b4ae5b7fc24787cc6e4b9", + "model_id": "6eba31b6c28b4e34a843b3251d24462d", "version_major": 2, "version_minor": 0 }, @@ -946,7 +978,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "ce8cd01863bc48a19d26e532aab71e34", + "model_id": "aebf90900b784e80a835ec5e32acad52", "version_major": 2, "version_minor": 0 }, @@ -960,7 +992,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - 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Ethical Considerations

} } var slices_all = JSON.parse("{\"0\": [\"metric:Accuracy\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"1\": [\"metric:Precision\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"2\": [\"metric:Recall\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"3\": [\"metric:F1 Score\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"4\": [\"metric:AUROC\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"5\": [\"metric:Accuracy\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"6\": [\"metric:Precision\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"7\": [\"metric:Recall\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"8\": [\"metric:F1 Score\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"9\": [\"metric:AUROC\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"10\": [\"metric:Accuracy\", \"gender:M\", \"age:overall_age\"], \"11\": [\"metric:Precision\", \"gender:M\", \"age:overall_age\"], \"12\": [\"metric:Recall\", \"gender:M\", \"age:overall_age\"], \"13\": [\"metric:F1 Score\", \"gender:M\", \"age:overall_age\"], \"14\": [\"metric:AUROC\", \"gender:M\", \"age:overall_age\"], \"15\": [\"metric:Accuracy\", \"gender:F\", \"age:overall_age\"], \"16\": [\"metric:Precision\", \"gender:F\", \"age:overall_age\"], \"17\": [\"metric:Recall\", \"gender:F\", \"age:overall_age\"], \"18\": [\"metric:F1 Score\", \"gender:F\", \"age:overall_age\"], \"19\": [\"metric:AUROC\", \"gender:F\", \"age:overall_age\"], \"20\": [\"metric:Accuracy\", \"age:overall_age\", \"gender:overall_gender\"], \"21\": [\"metric:Precision\", \"age:overall_age\", \"gender:overall_gender\"], \"22\": [\"metric:Recall\", \"age:overall_age\", \"gender:overall_gender\"], \"23\": [\"metric:F1 Score\", \"age:overall_age\", \"gender:overall_gender\"], \"24\": [\"metric:AUROC\", \"age:overall_age\", \"gender:overall_gender\"]}"); - var histories_all = JSON.parse("{\"0\": [\"0.9166666865348816\", \"0.8397180644181766\", \"0.8468964169885375\", \"0.912784682884717\", \"0.858758769113928\"], \"1\": [\"1.0\", \"0.9005789330532981\", \"0.8456640951819103\", \"0.8943705465573766\", \"0.8817889045551556\"], \"2\": [\"0.8571428656578064\", \"0.8708624635093035\", \"0.8209258988935838\", \"0.7081222342208849\", \"0.8741448002750659\"], \"3\": [\"0.9230769276618958\", \"0.9013738957623176\", \"0.9777632183234674\", \"1.0\", \"0.937534854767178\"], \"4\": [\"0.9654321074485779\", \"0.8644568384899219\", \"0.9038135503890949\", \"0.9805047978034174\", \"0.8791301037217211\"], \"5\": [\"0.8793103694915771\", \"0.8774980787834252\", \"0.7547610712651001\", \"0.8499825261231906\", \"0.924893444218657\"], \"6\": [\"0.9230769276618958\", \"0.8774939629799089\", \"1.0\", \"0.8649664220930133\", \"0.6994648769597892\"], \"7\": [\"0.8275862336158752\", \"0.9258526315266651\", \"0.9921829451771501\", \"1.0\", \"1.0\"], \"8\": [\"0.8727272748947144\", \"0.9212950991773885\", \"0.7085695212590467\", \"0.658855191983462\", \"0.6751820887851172\"], \"9\": [\"0.9589774012565613\", \"0.8761374258225499\", \"0.7751066707819452\", \"0.8095115387500368\", \"0.8240241365263508\"], \"10\": [\"0.9304347634315491\", \"0.8306382078926106\", \"0.9956936640757825\", \"1.0\", \"1.0\"], \"11\": [\"1.0\", \"1.0\", \"1.0\", \"1.0\", \"1.0\"], \"12\": [\"0.8857142925262451\", \"0.9868284976412902\", \"0.8121777334378891\", \"0.6774208043330758\", \"0.64722909410425\"], \"13\": [\"0.939393937587738\", \"0.795219440019655\", \"0.8125361706977661\", \"0.6279121368929667\", \"0.6829768720330566\"], \"14\": [\"0.9680952429771423\", \"1.0\", \"1.0\", \"1.0\", \"0.9822540027014691\"], \"15\": [\"0.8918918967247009\", \"0.8760944668145522\", \"1.0\", \"1.0\", \"1.0\"], \"16\": [\"0.9701492786407471\", \"1.0\", \"1.0\", \"0.9339353029935711\", \"0.8335633421651423\"], \"17\": [\"0.8666666746139526\", \"0.744316615004317\", \"0.6952540800415027\", \"0.6817061845080393\", \"0.6086783495769349\"], \"18\": [\"0.9154929518699646\", \"0.7354961661203616\", \"0.7859539286503151\", \"1.0\", \"1.0\"], \"19\": [\"0.9657407402992249\", \"1.0\", \"0.8647296539294258\", \"0.7990228951579779\", \"0.8943418632952396\"], \"20\": [\"0.9115044474601746\", \"0.9467944843026669\", \"0.9734478335269036\", \"1.0\", \"0.8346555378225913\"], \"21\": [\"0.9844961166381836\", \"1.0\", \"0.9869028743785946\", \"1.0\", \"1.0\"], \"22\": [\"0.8758620619773865\", \"0.8058996613040379\", \"0.8320408659798584\", \"0.850249055817879\", \"0.8508578877787705\"], \"23\": [\"0.9270073175430298\", \"0.9233027476005723\", \"0.7929189229829988\", \"0.8607432389347\", \"0.7808287456374037\"], \"24\": [\"0.9676032662391663\", \"0.9586476043589423\", \"0.8609395369927462\", \"0.894409193303693\", \"0.8976272397936238\"]}"); + var histories_all = JSON.parse("{\"0\": [\"0.8799999952316284\", \"0.8664143332362659\", \"0.9628365999094651\", \"0.9197934108330714\", \"0.8419300327025626\"], \"1\": [\"1.0\", \"0.7731663253792974\", \"0.8261070090900765\", \"0.9210264037393365\", \"0.8903242357040236\"], \"2\": [\"0.7966101765632629\", \"0.6191129555177851\", \"0.6916798374131509\", \"0.7761101153479317\", \"0.744749258353501\"], \"3\": [\"0.8867924809455872\", \"0.844810612458737\", \"0.825576061768424\", \"0.7643691811391724\", \"0.8472594551758559\"], \"4\": [\"0.9377841949462891\", \"0.8544685307615489\", \"0.8849093331335\", \"1.0\", \"1.0\"], \"5\": [\"0.9047619104385376\", \"0.9840070677500377\", \"0.853283357308065\", \"1.0\", \"1.0\"], \"6\": [\"0.90625\", \"0.7242083705906494\", \"0.8875334680476953\", \"0.811896982996081\", \"0.8240282461349576\"], \"7\": [\"0.90625\", \"0.9734510244227543\", \"0.9260109269751525\", \"1.0\", \"0.8194119526292629\"], \"8\": [\"0.90625\", \"1.0\", \"0.8207048819211085\", \"0.9039792424579787\", \"0.9436241482606225\"], \"9\": [\"0.9495968222618103\", \"0.881263044827248\", \"0.7515884782578613\", \"0.7606417497864129\", \"0.6853838273738471\"], \"10\": [\"0.9304347634315491\", \"0.9296849588017435\", \"0.8962427333840577\", \"0.8897399146107404\", \"0.9263904688607301\"], \"11\": [\"1.0\", \"0.873534323528482\", \"0.9891830751456437\", \"1.0\", \"0.9933051239365243\"], \"12\": [\"0.8904109597206116\", \"1.0\", \"1.0\", \"0.9642132238565819\", \"1.0\"], \"13\": [\"0.9420289993286133\", \"0.9938115969316876\", \"0.8096524110426412\", \"0.8287681177373631\", \"0.9417535559150443\"], \"14\": [\"0.9721134901046753\", \"0.924245544801077\", \"0.7206123055464732\", \"0.6356485516993373\", \"0.47897173668695836\"], \"15\": [\"0.8558558821678162\", \"0.86695538872542\", \"0.8120037808874143\", \"0.7051724802486516\", \"0.7921128283871254\"], \"16\": [\"0.9375\", \"0.9209185365749137\", \"1.0\", \"0.9361611889293945\", \"1.0\"], \"17\": [\"0.8333333134651184\", \"0.6608632534158778\", \"0.6559805069931867\", \"0.43817511738012793\", \"0.4574870206568118\"], \"18\": [\"0.8823529481887817\", \"0.8854525366363961\", \"0.804915966423132\", \"0.7927029764956607\", \"0.6974729962849618\"], \"19\": [\"0.9471153616905212\", \"1.0\", \"1.0\", \"0.9880693749621365\", \"1.0\"], \"20\": [\"0.8938053250312805\", \"0.9341693778790047\", \"1.0\", \"1.0\", \"1.0\"], \"21\": [\"0.9689922332763672\", \"0.8502121924415352\", \"0.8370212694364199\", \"0.6306127883809782\", \"0.5872940622328046\"], \"22\": [\"0.8620689511299133\", \"0.8950170755961049\", \"0.9553916766941566\", \"1.0\", \"1.0\"], \"23\": [\"0.9124087691307068\", \"1.0\", \"0.9165148792292718\", \"0.9851651501765221\", \"0.9347442836271158\"], \"24\": [\"0.9588761329650879\", \"0.9199750432222027\", \"1.0\", \"1.0\", \"0.8099604476116062\"]}"); var thresholds_all = JSON.parse("{\"0\": \"0.7\", \"1\": \"0.7\", \"2\": \"0.7\", \"3\": \"0.7\", \"4\": \"0.7\", \"5\": \"0.7\", \"6\": \"0.7\", \"7\": \"0.7\", \"8\": \"0.7\", \"9\": \"0.7\", \"10\": \"0.7\", \"11\": \"0.7\", \"12\": \"0.7\", \"13\": \"0.7\", \"14\": \"0.7\", \"15\": \"0.7\", \"16\": \"0.7\", \"17\": \"0.7\", \"18\": \"0.7\", \"19\": \"0.7\", \"20\": \"0.7\", \"21\": \"0.7\", \"22\": \"0.7\", \"23\": \"0.7\", \"24\": \"0.7\"}"); - var passed_all = JSON.parse("{\"0\": true, \"1\": true, \"2\": true, \"3\": true, \"4\": true, \"5\": true, \"6\": false, \"7\": true, \"8\": false, \"9\": true, \"10\": true, \"11\": true, \"12\": false, \"13\": false, \"14\": true, \"15\": true, \"16\": true, \"17\": false, \"18\": true, \"19\": true, \"20\": true, \"21\": true, \"22\": true, \"23\": true, \"24\": true}"); + var passed_all = JSON.parse("{\"0\": true, \"1\": true, \"2\": true, \"3\": true, \"4\": true, \"5\": true, \"6\": true, \"7\": true, \"8\": true, \"9\": false, \"10\": true, \"11\": true, \"12\": true, \"13\": true, \"14\": false, \"15\": true, \"16\": true, \"17\": false, \"18\": false, \"19\": true, \"20\": true, \"21\": false, \"22\": true, \"23\": true, \"24\": true}"); var names_all = JSON.parse("{\"0\": \"Accuracy\", \"1\": \"Precision\", \"2\": \"Recall\", \"3\": \"F1 Score\", \"4\": \"AUROC\", \"5\": \"Accuracy\", \"6\": \"Precision\", \"7\": \"Recall\", \"8\": \"F1 Score\", \"9\": \"AUROC\", \"10\": \"Accuracy\", \"11\": \"Precision\", \"12\": \"Recall\", \"13\": \"F1 Score\", \"14\": \"AUROC\", \"15\": \"Accuracy\", \"16\": \"Precision\", \"17\": \"Recall\", \"18\": \"F1 Score\", \"19\": \"AUROC\", \"20\": \"Accuracy\", \"21\": \"Precision\", \"22\": \"Recall\", \"23\": \"F1 Score\", \"24\": \"AUROC\"}"); var timestamps_all = JSON.parse("{\"0\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"1\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"2\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"3\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"4\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"5\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"6\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"7\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"8\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"9\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"10\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"11\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"12\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"13\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"14\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"15\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"16\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"17\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"18\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"19\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"20\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"21\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"22\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"23\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"24\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"]}"); @@ -2407,7 +2407,7 @@

Ethical Considerations

function generate_model_card_plot() { var model_card_plots = [] var overall_indices = [20, 21, 22, 23, 24] - var histories = JSON.parse("{\"0\": [\"0.9166666865348816\", \"0.8397180644181766\", \"0.8468964169885375\", \"0.912784682884717\", \"0.858758769113928\"], \"1\": [\"1.0\", \"0.9005789330532981\", \"0.8456640951819103\", \"0.8943705465573766\", \"0.8817889045551556\"], \"2\": [\"0.8571428656578064\", \"0.8708624635093035\", \"0.8209258988935838\", \"0.7081222342208849\", \"0.8741448002750659\"], \"3\": [\"0.9230769276618958\", \"0.9013738957623176\", \"0.9777632183234674\", \"1.0\", \"0.937534854767178\"], \"4\": [\"0.9654321074485779\", \"0.8644568384899219\", \"0.9038135503890949\", \"0.9805047978034174\", \"0.8791301037217211\"], \"5\": [\"0.8793103694915771\", \"0.8774980787834252\", \"0.7547610712651001\", \"0.8499825261231906\", \"0.924893444218657\"], \"6\": [\"0.9230769276618958\", \"0.8774939629799089\", \"1.0\", \"0.8649664220930133\", \"0.6994648769597892\"], \"7\": [\"0.8275862336158752\", \"0.9258526315266651\", \"0.9921829451771501\", \"1.0\", \"1.0\"], \"8\": [\"0.8727272748947144\", \"0.9212950991773885\", \"0.7085695212590467\", \"0.658855191983462\", \"0.6751820887851172\"], \"9\": [\"0.9589774012565613\", \"0.8761374258225499\", \"0.7751066707819452\", \"0.8095115387500368\", \"0.8240241365263508\"], \"10\": [\"0.9304347634315491\", \"0.8306382078926106\", \"0.9956936640757825\", \"1.0\", \"1.0\"], \"11\": [\"1.0\", \"1.0\", \"1.0\", \"1.0\", \"1.0\"], \"12\": [\"0.8857142925262451\", \"0.9868284976412902\", \"0.8121777334378891\", \"0.6774208043330758\", \"0.64722909410425\"], \"13\": [\"0.939393937587738\", \"0.795219440019655\", \"0.8125361706977661\", \"0.6279121368929667\", \"0.6829768720330566\"], \"14\": [\"0.9680952429771423\", \"1.0\", \"1.0\", \"1.0\", \"0.9822540027014691\"], \"15\": [\"0.8918918967247009\", \"0.8760944668145522\", \"1.0\", \"1.0\", \"1.0\"], \"16\": [\"0.9701492786407471\", \"1.0\", \"1.0\", \"0.9339353029935711\", \"0.8335633421651423\"], \"17\": [\"0.8666666746139526\", \"0.744316615004317\", \"0.6952540800415027\", \"0.6817061845080393\", \"0.6086783495769349\"], \"18\": [\"0.9154929518699646\", \"0.7354961661203616\", \"0.7859539286503151\", \"1.0\", \"1.0\"], \"19\": [\"0.9657407402992249\", \"1.0\", \"0.8647296539294258\", \"0.7990228951579779\", \"0.8943418632952396\"], \"20\": [\"0.9115044474601746\", \"0.9467944843026669\", \"0.9734478335269036\", \"1.0\", \"0.8346555378225913\"], \"21\": [\"0.9844961166381836\", \"1.0\", \"0.9869028743785946\", \"1.0\", \"1.0\"], \"22\": [\"0.8758620619773865\", \"0.8058996613040379\", \"0.8320408659798584\", \"0.850249055817879\", \"0.8508578877787705\"], \"23\": [\"0.9270073175430298\", \"0.9233027476005723\", \"0.7929189229829988\", \"0.8607432389347\", \"0.7808287456374037\"], \"24\": [\"0.9676032662391663\", \"0.9586476043589423\", \"0.8609395369927462\", \"0.894409193303693\", \"0.8976272397936238\"]}"); + var histories = JSON.parse("{\"0\": [\"0.8799999952316284\", \"0.8664143332362659\", \"0.9628365999094651\", \"0.9197934108330714\", \"0.8419300327025626\"], \"1\": [\"1.0\", \"0.7731663253792974\", \"0.8261070090900765\", \"0.9210264037393365\", \"0.8903242357040236\"], \"2\": [\"0.7966101765632629\", \"0.6191129555177851\", \"0.6916798374131509\", \"0.7761101153479317\", \"0.744749258353501\"], \"3\": [\"0.8867924809455872\", \"0.844810612458737\", \"0.825576061768424\", \"0.7643691811391724\", \"0.8472594551758559\"], \"4\": [\"0.9377841949462891\", \"0.8544685307615489\", \"0.8849093331335\", \"1.0\", \"1.0\"], \"5\": [\"0.9047619104385376\", \"0.9840070677500377\", \"0.853283357308065\", \"1.0\", \"1.0\"], \"6\": [\"0.90625\", \"0.7242083705906494\", \"0.8875334680476953\", \"0.811896982996081\", \"0.8240282461349576\"], \"7\": [\"0.90625\", \"0.9734510244227543\", \"0.9260109269751525\", \"1.0\", \"0.8194119526292629\"], \"8\": [\"0.90625\", \"1.0\", \"0.8207048819211085\", \"0.9039792424579787\", \"0.9436241482606225\"], \"9\": [\"0.9495968222618103\", \"0.881263044827248\", \"0.7515884782578613\", \"0.7606417497864129\", \"0.6853838273738471\"], \"10\": [\"0.9304347634315491\", \"0.9296849588017435\", \"0.8962427333840577\", \"0.8897399146107404\", \"0.9263904688607301\"], \"11\": [\"1.0\", \"0.873534323528482\", \"0.9891830751456437\", \"1.0\", \"0.9933051239365243\"], \"12\": [\"0.8904109597206116\", \"1.0\", \"1.0\", \"0.9642132238565819\", \"1.0\"], \"13\": [\"0.9420289993286133\", \"0.9938115969316876\", \"0.8096524110426412\", \"0.8287681177373631\", \"0.9417535559150443\"], \"14\": [\"0.9721134901046753\", \"0.924245544801077\", \"0.7206123055464732\", \"0.6356485516993373\", \"0.47897173668695836\"], \"15\": [\"0.8558558821678162\", \"0.86695538872542\", \"0.8120037808874143\", \"0.7051724802486516\", \"0.7921128283871254\"], \"16\": [\"0.9375\", \"0.9209185365749137\", \"1.0\", \"0.9361611889293945\", \"1.0\"], \"17\": [\"0.8333333134651184\", \"0.6608632534158778\", \"0.6559805069931867\", \"0.43817511738012793\", \"0.4574870206568118\"], \"18\": [\"0.8823529481887817\", \"0.8854525366363961\", \"0.804915966423132\", \"0.7927029764956607\", \"0.6974729962849618\"], \"19\": [\"0.9471153616905212\", \"1.0\", \"1.0\", \"0.9880693749621365\", \"1.0\"], \"20\": [\"0.8938053250312805\", \"0.9341693778790047\", \"1.0\", \"1.0\", \"1.0\"], \"21\": [\"0.9689922332763672\", \"0.8502121924415352\", \"0.8370212694364199\", \"0.6306127883809782\", \"0.5872940622328046\"], \"22\": [\"0.8620689511299133\", \"0.8950170755961049\", \"0.9553916766941566\", \"1.0\", \"1.0\"], \"23\": [\"0.9124087691307068\", \"1.0\", \"0.9165148792292718\", \"0.9851651501765221\", \"0.9347442836271158\"], \"24\": [\"0.9588761329650879\", \"0.9199750432222027\", \"1.0\", \"1.0\", \"0.8099604476116062\"]}"); var thresholds = JSON.parse("{\"0\": \"0.7\", \"1\": \"0.7\", \"2\": \"0.7\", \"3\": \"0.7\", \"4\": \"0.7\", \"5\": \"0.7\", \"6\": \"0.7\", \"7\": \"0.7\", \"8\": \"0.7\", \"9\": \"0.7\", \"10\": \"0.7\", \"11\": \"0.7\", \"12\": \"0.7\", \"13\": \"0.7\", \"14\": \"0.7\", \"15\": \"0.7\", \"16\": \"0.7\", \"17\": \"0.7\", \"18\": \"0.7\", \"19\": \"0.7\", \"20\": \"0.7\", \"21\": \"0.7\", \"22\": \"0.7\", \"23\": \"0.7\", \"24\": \"0.7\"}"); var timestamps = JSON.parse("{\"0\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"1\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"2\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"3\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"4\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"5\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"6\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"7\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"8\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"9\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"10\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"11\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"12\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"13\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"14\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"15\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"16\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"17\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"18\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"19\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"20\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"21\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"22\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"23\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"24\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"]}"); @@ -2623,9 +2623,9 @@

Ethical Considerations

} } var slices_all = JSON.parse("{\"0\": [\"metric:Accuracy\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"1\": [\"metric:Precision\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"2\": [\"metric:Recall\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"3\": [\"metric:F1 Score\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"4\": [\"metric:AUROC\", \"age:[20 - 50)\", \"gender:overall_gender\"], \"5\": [\"metric:Accuracy\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"6\": [\"metric:Precision\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"7\": [\"metric:Recall\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"8\": [\"metric:F1 Score\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"9\": [\"metric:AUROC\", \"age:[50 - 80)\", \"gender:overall_gender\"], \"10\": [\"metric:Accuracy\", \"gender:M\", \"age:overall_age\"], \"11\": [\"metric:Precision\", \"gender:M\", \"age:overall_age\"], \"12\": [\"metric:Recall\", \"gender:M\", \"age:overall_age\"], \"13\": [\"metric:F1 Score\", \"gender:M\", \"age:overall_age\"], \"14\": [\"metric:AUROC\", \"gender:M\", \"age:overall_age\"], \"15\": [\"metric:Accuracy\", \"gender:F\", \"age:overall_age\"], \"16\": [\"metric:Precision\", \"gender:F\", \"age:overall_age\"], \"17\": [\"metric:Recall\", \"gender:F\", \"age:overall_age\"], \"18\": [\"metric:F1 Score\", \"gender:F\", \"age:overall_age\"], \"19\": [\"metric:AUROC\", \"gender:F\", \"age:overall_age\"], \"20\": [\"metric:Accuracy\", \"age:overall_age\", \"gender:overall_gender\"], \"21\": [\"metric:Precision\", \"age:overall_age\", \"gender:overall_gender\"], \"22\": [\"metric:Recall\", \"age:overall_age\", \"gender:overall_gender\"], \"23\": [\"metric:F1 Score\", \"age:overall_age\", \"gender:overall_gender\"], \"24\": [\"metric:AUROC\", \"age:overall_age\", \"gender:overall_gender\"]}"); - var histories_all = JSON.parse("{\"0\": [\"0.9166666865348816\", \"0.8397180644181766\", \"0.8468964169885375\", \"0.912784682884717\", \"0.858758769113928\"], \"1\": [\"1.0\", \"0.9005789330532981\", \"0.8456640951819103\", \"0.8943705465573766\", \"0.8817889045551556\"], \"2\": [\"0.8571428656578064\", \"0.8708624635093035\", \"0.8209258988935838\", \"0.7081222342208849\", \"0.8741448002750659\"], \"3\": [\"0.9230769276618958\", \"0.9013738957623176\", \"0.9777632183234674\", \"1.0\", \"0.937534854767178\"], \"4\": [\"0.9654321074485779\", \"0.8644568384899219\", \"0.9038135503890949\", \"0.9805047978034174\", \"0.8791301037217211\"], \"5\": [\"0.8793103694915771\", \"0.8774980787834252\", \"0.7547610712651001\", \"0.8499825261231906\", \"0.924893444218657\"], \"6\": [\"0.9230769276618958\", \"0.8774939629799089\", \"1.0\", \"0.8649664220930133\", \"0.6994648769597892\"], \"7\": [\"0.8275862336158752\", \"0.9258526315266651\", \"0.9921829451771501\", \"1.0\", \"1.0\"], \"8\": [\"0.8727272748947144\", \"0.9212950991773885\", \"0.7085695212590467\", \"0.658855191983462\", \"0.6751820887851172\"], \"9\": [\"0.9589774012565613\", \"0.8761374258225499\", \"0.7751066707819452\", \"0.8095115387500368\", \"0.8240241365263508\"], \"10\": [\"0.9304347634315491\", \"0.8306382078926106\", \"0.9956936640757825\", \"1.0\", \"1.0\"], \"11\": [\"1.0\", \"1.0\", \"1.0\", \"1.0\", \"1.0\"], \"12\": [\"0.8857142925262451\", \"0.9868284976412902\", \"0.8121777334378891\", \"0.6774208043330758\", \"0.64722909410425\"], \"13\": [\"0.939393937587738\", \"0.795219440019655\", \"0.8125361706977661\", \"0.6279121368929667\", \"0.6829768720330566\"], \"14\": [\"0.9680952429771423\", \"1.0\", \"1.0\", \"1.0\", \"0.9822540027014691\"], \"15\": [\"0.8918918967247009\", \"0.8760944668145522\", \"1.0\", \"1.0\", \"1.0\"], \"16\": [\"0.9701492786407471\", \"1.0\", \"1.0\", \"0.9339353029935711\", \"0.8335633421651423\"], \"17\": [\"0.8666666746139526\", \"0.744316615004317\", \"0.6952540800415027\", \"0.6817061845080393\", \"0.6086783495769349\"], \"18\": [\"0.9154929518699646\", \"0.7354961661203616\", \"0.7859539286503151\", \"1.0\", \"1.0\"], \"19\": [\"0.9657407402992249\", \"1.0\", \"0.8647296539294258\", \"0.7990228951579779\", \"0.8943418632952396\"], \"20\": [\"0.9115044474601746\", \"0.9467944843026669\", \"0.9734478335269036\", \"1.0\", \"0.8346555378225913\"], \"21\": [\"0.9844961166381836\", \"1.0\", \"0.9869028743785946\", \"1.0\", \"1.0\"], \"22\": [\"0.8758620619773865\", \"0.8058996613040379\", \"0.8320408659798584\", \"0.850249055817879\", \"0.8508578877787705\"], \"23\": [\"0.9270073175430298\", \"0.9233027476005723\", \"0.7929189229829988\", \"0.8607432389347\", \"0.7808287456374037\"], \"24\": [\"0.9676032662391663\", \"0.9586476043589423\", \"0.8609395369927462\", \"0.894409193303693\", \"0.8976272397936238\"]}"); + var histories_all = JSON.parse("{\"0\": [\"0.8799999952316284\", \"0.8664143332362659\", \"0.9628365999094651\", \"0.9197934108330714\", \"0.8419300327025626\"], \"1\": [\"1.0\", \"0.7731663253792974\", \"0.8261070090900765\", \"0.9210264037393365\", \"0.8903242357040236\"], \"2\": [\"0.7966101765632629\", \"0.6191129555177851\", \"0.6916798374131509\", \"0.7761101153479317\", \"0.744749258353501\"], \"3\": [\"0.8867924809455872\", \"0.844810612458737\", \"0.825576061768424\", \"0.7643691811391724\", \"0.8472594551758559\"], \"4\": [\"0.9377841949462891\", \"0.8544685307615489\", \"0.8849093331335\", \"1.0\", \"1.0\"], \"5\": [\"0.9047619104385376\", \"0.9840070677500377\", \"0.853283357308065\", \"1.0\", \"1.0\"], \"6\": [\"0.90625\", \"0.7242083705906494\", \"0.8875334680476953\", \"0.811896982996081\", \"0.8240282461349576\"], \"7\": [\"0.90625\", \"0.9734510244227543\", \"0.9260109269751525\", \"1.0\", \"0.8194119526292629\"], \"8\": [\"0.90625\", \"1.0\", \"0.8207048819211085\", \"0.9039792424579787\", \"0.9436241482606225\"], \"9\": [\"0.9495968222618103\", \"0.881263044827248\", \"0.7515884782578613\", \"0.7606417497864129\", \"0.6853838273738471\"], \"10\": [\"0.9304347634315491\", \"0.9296849588017435\", \"0.8962427333840577\", \"0.8897399146107404\", \"0.9263904688607301\"], \"11\": [\"1.0\", \"0.873534323528482\", \"0.9891830751456437\", \"1.0\", \"0.9933051239365243\"], \"12\": [\"0.8904109597206116\", \"1.0\", \"1.0\", \"0.9642132238565819\", \"1.0\"], \"13\": [\"0.9420289993286133\", \"0.9938115969316876\", \"0.8096524110426412\", \"0.8287681177373631\", \"0.9417535559150443\"], \"14\": [\"0.9721134901046753\", \"0.924245544801077\", \"0.7206123055464732\", \"0.6356485516993373\", \"0.47897173668695836\"], \"15\": [\"0.8558558821678162\", \"0.86695538872542\", \"0.8120037808874143\", \"0.7051724802486516\", \"0.7921128283871254\"], \"16\": [\"0.9375\", \"0.9209185365749137\", \"1.0\", \"0.9361611889293945\", \"1.0\"], \"17\": [\"0.8333333134651184\", \"0.6608632534158778\", \"0.6559805069931867\", \"0.43817511738012793\", \"0.4574870206568118\"], \"18\": [\"0.8823529481887817\", \"0.8854525366363961\", \"0.804915966423132\", \"0.7927029764956607\", \"0.6974729962849618\"], \"19\": [\"0.9471153616905212\", \"1.0\", \"1.0\", \"0.9880693749621365\", \"1.0\"], \"20\": [\"0.8938053250312805\", \"0.9341693778790047\", \"1.0\", \"1.0\", \"1.0\"], \"21\": [\"0.9689922332763672\", \"0.8502121924415352\", \"0.8370212694364199\", \"0.6306127883809782\", \"0.5872940622328046\"], \"22\": [\"0.8620689511299133\", \"0.8950170755961049\", \"0.9553916766941566\", \"1.0\", \"1.0\"], \"23\": [\"0.9124087691307068\", \"1.0\", \"0.9165148792292718\", \"0.9851651501765221\", \"0.9347442836271158\"], \"24\": [\"0.9588761329650879\", \"0.9199750432222027\", \"1.0\", \"1.0\", \"0.8099604476116062\"]}"); var thresholds_all = JSON.parse("{\"0\": \"0.7\", \"1\": \"0.7\", \"2\": \"0.7\", \"3\": \"0.7\", \"4\": \"0.7\", \"5\": \"0.7\", \"6\": \"0.7\", \"7\": \"0.7\", \"8\": \"0.7\", \"9\": \"0.7\", \"10\": \"0.7\", \"11\": \"0.7\", \"12\": \"0.7\", \"13\": \"0.7\", \"14\": \"0.7\", \"15\": \"0.7\", \"16\": \"0.7\", \"17\": \"0.7\", \"18\": \"0.7\", \"19\": \"0.7\", \"20\": \"0.7\", \"21\": \"0.7\", \"22\": \"0.7\", \"23\": \"0.7\", \"24\": \"0.7\"}"); - var passed_all = JSON.parse("{\"0\": true, \"1\": true, \"2\": true, \"3\": true, \"4\": true, \"5\": true, \"6\": false, \"7\": true, \"8\": false, \"9\": true, \"10\": true, \"11\": true, \"12\": false, \"13\": false, \"14\": true, \"15\": true, \"16\": true, \"17\": false, \"18\": true, \"19\": true, \"20\": true, \"21\": true, \"22\": true, \"23\": true, \"24\": true}"); + var passed_all = JSON.parse("{\"0\": true, \"1\": true, \"2\": true, \"3\": true, \"4\": true, \"5\": true, \"6\": true, \"7\": true, \"8\": true, \"9\": false, \"10\": true, \"11\": true, \"12\": true, \"13\": true, \"14\": false, \"15\": true, \"16\": true, \"17\": false, \"18\": false, \"19\": true, \"20\": true, \"21\": false, \"22\": true, \"23\": true, \"24\": true}"); var names_all = JSON.parse("{\"0\": \"Accuracy\", \"1\": \"Precision\", \"2\": \"Recall\", \"3\": \"F1 Score\", \"4\": \"AUROC\", \"5\": \"Accuracy\", \"6\": \"Precision\", \"7\": \"Recall\", \"8\": \"F1 Score\", \"9\": \"AUROC\", \"10\": \"Accuracy\", \"11\": \"Precision\", \"12\": \"Recall\", \"13\": \"F1 Score\", \"14\": \"AUROC\", \"15\": \"Accuracy\", \"16\": \"Precision\", \"17\": \"Recall\", \"18\": \"F1 Score\", \"19\": \"AUROC\", \"20\": \"Accuracy\", \"21\": \"Precision\", \"22\": \"Recall\", \"23\": \"F1 Score\", \"24\": \"AUROC\"}"); var timestamps_all = JSON.parse("{\"0\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"1\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"2\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"3\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"4\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"5\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"6\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"7\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"8\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"9\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"10\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"11\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"12\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"13\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"14\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"15\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"16\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"17\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"18\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"19\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"20\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"21\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"22\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"23\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"], \"24\": [\"2021-09-01\", \"2021-10-01\", \"2021-11-01\", \"2021-12-01\", \"2022-01-01\"]}"); @@ -3024,7 +3024,7 @@

Ethical Considerations

]; // create global variable for max_n_evals - var histories = JSON.parse("{\"0\": [\"0.9166666865348816\", \"0.8397180644181766\", \"0.8468964169885375\", \"0.912784682884717\", \"0.858758769113928\"], \"1\": [\"1.0\", \"0.9005789330532981\", \"0.8456640951819103\", \"0.8943705465573766\", \"0.8817889045551556\"], \"2\": [\"0.8571428656578064\", \"0.8708624635093035\", \"0.8209258988935838\", \"0.7081222342208849\", \"0.8741448002750659\"], \"3\": [\"0.9230769276618958\", \"0.9013738957623176\", \"0.9777632183234674\", \"1.0\", \"0.937534854767178\"], \"4\": [\"0.9654321074485779\", \"0.8644568384899219\", \"0.9038135503890949\", \"0.9805047978034174\", \"0.8791301037217211\"], \"5\": [\"0.8793103694915771\", \"0.8774980787834252\", \"0.7547610712651001\", \"0.8499825261231906\", \"0.924893444218657\"], \"6\": [\"0.9230769276618958\", \"0.8774939629799089\", \"1.0\", \"0.8649664220930133\", \"0.6994648769597892\"], \"7\": [\"0.8275862336158752\", \"0.9258526315266651\", \"0.9921829451771501\", \"1.0\", \"1.0\"], \"8\": [\"0.8727272748947144\", \"0.9212950991773885\", \"0.7085695212590467\", \"0.658855191983462\", \"0.6751820887851172\"], \"9\": [\"0.9589774012565613\", \"0.8761374258225499\", \"0.7751066707819452\", \"0.8095115387500368\", \"0.8240241365263508\"], \"10\": [\"0.9304347634315491\", \"0.8306382078926106\", \"0.9956936640757825\", \"1.0\", \"1.0\"], \"11\": [\"1.0\", \"1.0\", \"1.0\", \"1.0\", \"1.0\"], \"12\": [\"0.8857142925262451\", \"0.9868284976412902\", \"0.8121777334378891\", \"0.6774208043330758\", \"0.64722909410425\"], \"13\": [\"0.939393937587738\", \"0.795219440019655\", \"0.8125361706977661\", \"0.6279121368929667\", \"0.6829768720330566\"], \"14\": [\"0.9680952429771423\", \"1.0\", \"1.0\", \"1.0\", \"0.9822540027014691\"], \"15\": [\"0.8918918967247009\", \"0.8760944668145522\", \"1.0\", \"1.0\", \"1.0\"], \"16\": [\"0.9701492786407471\", \"1.0\", \"1.0\", \"0.9339353029935711\", \"0.8335633421651423\"], \"17\": [\"0.8666666746139526\", \"0.744316615004317\", \"0.6952540800415027\", \"0.6817061845080393\", \"0.6086783495769349\"], \"18\": [\"0.9154929518699646\", \"0.7354961661203616\", \"0.7859539286503151\", \"1.0\", \"1.0\"], \"19\": [\"0.9657407402992249\", \"1.0\", \"0.8647296539294258\", \"0.7990228951579779\", \"0.8943418632952396\"], \"20\": [\"0.9115044474601746\", \"0.9467944843026669\", \"0.9734478335269036\", \"1.0\", \"0.8346555378225913\"], \"21\": [\"0.9844961166381836\", \"1.0\", \"0.9869028743785946\", \"1.0\", \"1.0\"], \"22\": [\"0.8758620619773865\", \"0.8058996613040379\", \"0.8320408659798584\", \"0.850249055817879\", \"0.8508578877787705\"], \"23\": [\"0.9270073175430298\", \"0.9233027476005723\", \"0.7929189229829988\", \"0.8607432389347\", \"0.7808287456374037\"], \"24\": [\"0.9676032662391663\", \"0.9586476043589423\", \"0.8609395369927462\", \"0.894409193303693\", \"0.8976272397936238\"]}"); + var histories = JSON.parse("{\"0\": [\"0.8799999952316284\", \"0.8664143332362659\", \"0.9628365999094651\", \"0.9197934108330714\", \"0.8419300327025626\"], \"1\": [\"1.0\", \"0.7731663253792974\", \"0.8261070090900765\", \"0.9210264037393365\", \"0.8903242357040236\"], \"2\": [\"0.7966101765632629\", \"0.6191129555177851\", \"0.6916798374131509\", \"0.7761101153479317\", \"0.744749258353501\"], \"3\": [\"0.8867924809455872\", \"0.844810612458737\", \"0.825576061768424\", \"0.7643691811391724\", \"0.8472594551758559\"], \"4\": [\"0.9377841949462891\", \"0.8544685307615489\", \"0.8849093331335\", \"1.0\", \"1.0\"], \"5\": [\"0.9047619104385376\", \"0.9840070677500377\", \"0.853283357308065\", \"1.0\", \"1.0\"], \"6\": [\"0.90625\", \"0.7242083705906494\", \"0.8875334680476953\", \"0.811896982996081\", \"0.8240282461349576\"], \"7\": [\"0.90625\", \"0.9734510244227543\", \"0.9260109269751525\", \"1.0\", \"0.8194119526292629\"], \"8\": [\"0.90625\", \"1.0\", \"0.8207048819211085\", \"0.9039792424579787\", \"0.9436241482606225\"], \"9\": [\"0.9495968222618103\", \"0.881263044827248\", \"0.7515884782578613\", \"0.7606417497864129\", \"0.6853838273738471\"], \"10\": [\"0.9304347634315491\", \"0.9296849588017435\", \"0.8962427333840577\", \"0.8897399146107404\", \"0.9263904688607301\"], \"11\": [\"1.0\", \"0.873534323528482\", \"0.9891830751456437\", \"1.0\", \"0.9933051239365243\"], \"12\": [\"0.8904109597206116\", \"1.0\", \"1.0\", \"0.9642132238565819\", \"1.0\"], \"13\": [\"0.9420289993286133\", \"0.9938115969316876\", \"0.8096524110426412\", \"0.8287681177373631\", \"0.9417535559150443\"], \"14\": [\"0.9721134901046753\", \"0.924245544801077\", \"0.7206123055464732\", \"0.6356485516993373\", \"0.47897173668695836\"], \"15\": [\"0.8558558821678162\", \"0.86695538872542\", \"0.8120037808874143\", \"0.7051724802486516\", \"0.7921128283871254\"], \"16\": [\"0.9375\", \"0.9209185365749137\", \"1.0\", \"0.9361611889293945\", \"1.0\"], \"17\": [\"0.8333333134651184\", \"0.6608632534158778\", \"0.6559805069931867\", \"0.43817511738012793\", \"0.4574870206568118\"], \"18\": [\"0.8823529481887817\", \"0.8854525366363961\", \"0.804915966423132\", \"0.7927029764956607\", \"0.6974729962849618\"], \"19\": [\"0.9471153616905212\", \"1.0\", \"1.0\", \"0.9880693749621365\", \"1.0\"], \"20\": [\"0.8938053250312805\", \"0.9341693778790047\", \"1.0\", \"1.0\", \"1.0\"], \"21\": [\"0.9689922332763672\", \"0.8502121924415352\", \"0.8370212694364199\", \"0.6306127883809782\", \"0.5872940622328046\"], \"22\": [\"0.8620689511299133\", \"0.8950170755961049\", \"0.9553916766941566\", \"1.0\", \"1.0\"], \"23\": [\"0.9124087691307068\", \"1.0\", \"0.9165148792292718\", \"0.9851651501765221\", \"0.9347442836271158\"], \"24\": [\"0.9588761329650879\", \"0.9199750432222027\", \"1.0\", \"1.0\", \"0.8099604476116062\"]}"); // get max_n_evals from histories var history_data = []; for (let i = 0; i < histories[0].length; i++) { diff --git a/api/tutorials/synthea/los_prediction.html b/api/tutorials/synthea/los_prediction.html index 373c4a8ed..e391ac3b1 100644 --- a/api/tutorials/synthea/los_prediction.html +++ b/api/tutorials/synthea/los_prediction.html @@ -538,7 +538,7 @@

Compute length of stay (labels) 
-2024-04-05 15:07:38,019 INFO cycquery.orm    - Database setup, ready to run queries!
+2024-04-08 09:24:19,389 INFO cycquery.orm    - Database setup, ready to run queries!

@@ -546,7 +546,7 @@

Compute length of stay (labels) 
-2024-04-05 15:07:41,794 INFO cycquery.orm    - Query returned successfully!
+2024-04-08 09:24:22,635 INFO cycquery.orm    - Query returned successfully!

@@ -554,7 +554,7 @@

Compute length of stay (labels) 
-2024-04-05 15:07:41,795 INFO cycquery.utils.profile - Finished executing function run_query in 2.531621 s
+2024-04-08 09:24:22,636 INFO cycquery.utils.profile - Finished executing function run_query in 2.490392 s

@@ -562,7 +562,7 @@

Compute length of stay (labels) 
-2024-04-05 15:07:43,580 INFO cycquery.orm    - Query returned successfully!
+2024-04-08 09:24:24,410 INFO cycquery.orm    - Query returned successfully!

@@ -570,7 +570,7 @@

Compute length of stay (labels) 
-2024-04-05 15:07:43,582 INFO cycquery.utils.profile - Finished executing function run_query in 1.785541 s
+2024-04-08 09:24:24,411 INFO cycquery.utils.profile - Finished executing function run_query in 1.773785 s

@@ -578,7 +578,7 @@

Compute length of stay (labels) 
-2024-04-05 15:07:44,874 INFO cycquery.orm    - Query returned successfully!
+2024-04-08 09:24:25,651 INFO cycquery.orm    - Query returned successfully!

@@ -586,7 +586,7 @@

Compute length of stay (labels) 
-2024-04-05 15:07:44,875 INFO cycquery.utils.profile - Finished executing function run_query in 0.162420 s
+2024-04-08 09:24:25,653 INFO cycquery.utils.profile - Finished executing function run_query in 0.124331 s

@@ -594,7 +594,7 @@

Compute length of stay (labels) 
-2024-04-05 15:07:45,075 INFO cycquery.orm    - Query returned successfully!
+2024-04-08 09:24:25,821 INFO cycquery.orm    - Query returned successfully!

@@ -602,7 +602,7 @@

Compute length of stay (labels) 
-2024-04-05 15:07:45,077 INFO cycquery.utils.profile - Finished executing function run_query in 0.197449 s
+2024-04-08 09:24:25,822 INFO cycquery.utils.profile - Finished executing function run_query in 0.163747 s

@@ -610,7 +610,7 @@

Compute length of stay (labels) 
-2024-04-05 15:07:45,168 INFO cycquery.orm    - Query returned successfully!
+2024-04-08 09:24:25,908 INFO cycquery.orm    - Query returned successfully!

@@ -618,7 +618,7 @@

Compute length of stay (labels) 
-2024-04-05 15:07:45,170 INFO cycquery.utils.profile - Finished executing function run_query in 0.091991 s
+2024-04-08 09:24:25,909 INFO cycquery.utils.profile - Finished executing function run_query in 0.086249 s

@@ -671,9 +671,9 @@

Drop NaNs based on the
-
+
@@ -1235,7 +1235,7 @@

Training 
-2024-04-05 15:07:52,875 INFO cyclops.models.wrappers.sk_model - Best reg_lambda: 0
+2024-04-08 09:24:35,038 INFO cyclops.models.wrappers.sk_model - Best reg_lambda: 0
@@ -1243,7 +1243,7 @@

Training 

-2024-04-05 15:07:52,876 INFO cyclops.models.wrappers.sk_model - Best n_estimators: 500
+2024-04-08 09:24:35,039 INFO cyclops.models.wrappers.sk_model - Best n_estimators: 500
@@ -1251,7 +1251,7 @@

Training 

-2024-04-05 15:07:52,876 INFO cyclops.models.wrappers.sk_model - Best max_depth: 2
+2024-04-08 09:24:35,040 INFO cyclops.models.wrappers.sk_model - Best max_depth: 5
@@ -1259,7 +1259,7 @@

Training 

-2024-04-05 15:07:52,876 INFO cyclops.models.wrappers.sk_model - Best learning_rate: 0.01
+2024-04-08 09:24:35,040 INFO cyclops.models.wrappers.sk_model - Best learning_rate: 0.01
@@ -1267,7 +1267,7 @@

Training 

-2024-04-05 15:07:52,877 INFO cyclops.models.wrappers.sk_model - Best gamma: 1
+2024-04-08 09:24:35,040 INFO cyclops.models.wrappers.sk_model - Best gamma: 10
@@ -1275,7 +1275,7 @@

Training 

-2024-04-05 15:07:52,877 INFO cyclops.models.wrappers.sk_model - Best colsample_bytree: 0.7
+2024-04-08 09:24:35,041 INFO cyclops.models.wrappers.sk_model - Best colsample_bytree: 1
@@ -1688,26 +1688,26 @@

Training background-color: var(--sklearn-color-fitted-level-3); } 
XGBClassifier(base_score=None, booster=None, callbacks=None,
-              colsample_bylevel=None, colsample_bynode=None,
-              colsample_bytree=0.7, early_stopping_rounds=None,
-              enable_categorical=False, eval_metric='logloss',
-              feature_types=None, gamma=1, gpu_id=None, grow_policy=None,
-              importance_type=None, interaction_constraints=None,
-              learning_rate=0.01, max_bin=None, max_cat_threshold=None,
-              max_cat_to_onehot=None, max_delta_step=None, max_depth=2,
-              max_leaves=None, min_child_weight=3, missing=nan,
-              monotone_constraints=None, n_estimators=500, n_jobs=None,
-              num_parallel_tree=None, predictor=None, random_state=123, ...)
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.

+ colsample_bylevel=None, colsample_bynode=None, colsample_bytree=1, + early_stopping_rounds=None, enable_categorical=False, + eval_metric='logloss', feature_types=None, gamma=10, gpu_id=None, + grow_policy=None, importance_type=None, + interaction_constraints=None, learning_rate=0.01, max_bin=None, + max_cat_threshold=None, max_cat_to_onehot=None, + max_delta_step=None, max_depth=5, max_leaves=None, + min_child_weight=3, missing=nan, monotone_constraints=None, + n_estimators=500, n_jobs=None, num_parallel_tree=None, + predictor=None, random_state=123, ...)In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org. 
[27]:
@@ -1723,7 +1723,7 @@ 
Training
 
-{'objective': 'binary:logistic', 'use_label_encoder': None, 'base_score': None, 'booster': None, 'callbacks': None, 'colsample_bylevel': None, 'colsample_bynode': None, 'colsample_bytree': 0.7, 'early_stopping_rounds': None, 'enable_categorical': False, 'eval_metric': 'logloss', 'feature_types': None, 'gamma': 1, 'gpu_id': None, 'grow_policy': None, 'importance_type': None, 'interaction_constraints': None, 'learning_rate': 0.01, 'max_bin': None, 'max_cat_threshold': None, 'max_cat_to_onehot': None, 'max_delta_step': None, 'max_depth': 2, 'max_leaves': None, 'min_child_weight': 3, 'missing': nan, 'monotone_constraints': None, 'n_estimators': 500, 'n_jobs': None, 'num_parallel_tree': None, 'predictor': None, 'random_state': 123, 'reg_alpha': None, 'reg_lambda': 0, 'sampling_method': None, 'scale_pos_weight': None, 'subsample': None, 'tree_method': None, 'validate_parameters': None, 'verbosity': None, 'seed': 123}
+{'objective': 'binary:logistic', 'use_label_encoder': None, 'base_score': None, 'booster': None, 'callbacks': None, 'colsample_bylevel': None, 'colsample_bynode': None, 'colsample_bytree': 1, 'early_stopping_rounds': None, 'enable_categorical': False, 'eval_metric': 'logloss', 'feature_types': None, 'gamma': 10, 'gpu_id': None, 'grow_policy': None, 'importance_type': None, 'interaction_constraints': None, 'learning_rate': 0.01, 'max_bin': None, 'max_cat_threshold': None, 'max_cat_to_onehot': None, 'max_delta_step': None, 'max_depth': 5, 'max_leaves': None, 'min_child_weight': 3, 'missing': nan, 'monotone_constraints': None, 'n_estimators': 500, 'n_jobs': None, 'num_parallel_tree': None, 'predictor': None, 'random_state': 123, 'reg_alpha': None, 'reg_lambda': 0, 'sampling_method': None, 'scale_pos_weight': None, 'subsample': None, 'tree_method': None, 'validate_parameters': None, 'verbosity': None, 'seed': 123}

Log the model parameters to the report.

@@ -1759,7 +1759,7 @@

Prediction

-
+
@@ -1886,91 +1886,91 @@

Evaluation

-
+
-
+
-
+
-
+
-
+
-
+
-
+
-
+
-
+
-
+
-
+
-
+
-
+
-
+
-
+

Log the performance metrics to the report.

We can add a performance metric to the model card using the log_performance_metric method, which expects a dictionary where the keys are in the following format: slice_name/metric_name. For instance, overall/accuracy.

@@ -2073,9 +2073,9 @@

Evaluation
-

@@ -2574,5 +2574,7 @@

Report Generation + + \ No newline at end of file diff --git a/api/tutorials/synthea/los_prediction.ipynb b/api/tutorials/synthea/los_prediction.ipynb index a95741e13..7764f2626 100644 --- a/api/tutorials/synthea/los_prediction.ipynb +++ b/api/tutorials/synthea/los_prediction.ipynb @@ -33,10 +33,10 @@ "id": "53009e6b", "metadata": { "execution": { - "iopub.execute_input": "2024-04-05T19:07:32.578189Z", - "iopub.status.busy": "2024-04-05T19:07:32.577690Z", - "iopub.status.idle": "2024-04-05T19:07:37.112669Z", - "shell.execute_reply": "2024-04-05T19:07:37.111719Z" + "iopub.execute_input": "2024-04-08T13:24:14.038275Z", + "iopub.status.busy": "2024-04-08T13:24:14.037783Z", + "iopub.status.idle": "2024-04-08T13:24:18.557709Z", + "shell.execute_reply": "2024-04-08T13:24:18.556815Z" } }, "outputs": [], @@ -97,10 +97,10 @@ "id": "afae58a8-5708-4e05-8695-25ba3ce1a71f", "metadata": { "execution": { - "iopub.execute_input": "2024-04-05T19:07:37.118127Z", - "iopub.status.busy": "2024-04-05T19:07:37.117614Z", - "iopub.status.idle": "2024-04-05T19:07:37.121128Z", - "shell.execute_reply": "2024-04-05T19:07:37.120559Z" + "iopub.execute_input": "2024-04-08T13:24:18.563751Z", + "iopub.status.busy": "2024-04-08T13:24:18.563137Z", + "iopub.status.idle": "2024-04-08T13:24:18.568782Z", + "shell.execute_reply": "2024-04-08T13:24:18.567653Z" }, "tags": [] }, @@ -123,10 +123,10 @@ "id": "739b109a-011b-4e6e-a3de-964edeffddbd", "metadata": { "execution": { - "iopub.execute_input": "2024-04-05T19:07:37.126487Z", - "iopub.status.busy": "2024-04-05T19:07:37.126123Z", - "iopub.status.idle": "2024-04-05T19:07:37.129848Z", - "shell.execute_reply": "2024-04-05T19:07:37.129208Z" + "iopub.execute_input": "2024-04-08T13:24:18.574602Z", + "iopub.status.busy": "2024-04-08T13:24:18.574020Z", + "iopub.status.idle": "2024-04-08T13:24:18.580166Z", + "shell.execute_reply": "2024-04-08T13:24:18.578802Z" }, "tags": [] }, @@ -157,10 +157,10 @@ "id": "e497df9f-0f3d-4e9c-845c-539627a37f67", "metadata": { "execution": { - "iopub.execute_input": "2024-04-05T19:07:37.135272Z", - "iopub.status.busy": "2024-04-05T19:07:37.134827Z", - "iopub.status.idle": "2024-04-05T19:07:45.209199Z", - "shell.execute_reply": "2024-04-05T19:07:45.207884Z" + "iopub.execute_input": "2024-04-08T13:24:18.587402Z", + "iopub.status.busy": "2024-04-08T13:24:18.586349Z", + "iopub.status.idle": "2024-04-08T13:24:25.948332Z", + "shell.execute_reply": "2024-04-08T13:24:25.947469Z" }, "tags": [] }, @@ -169,77 +169,77 @@ "name": "stderr", "output_type": "stream", "text": [ - "2024-04-05 15:07:38,019 \u001b[1;37mINFO\u001b[0m cycquery.orm - Database setup, ready to run queries!\n" + "2024-04-08 09:24:19,389 \u001b[1;37mINFO\u001b[0m cycquery.orm - Database setup, ready to run queries!\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-05 15:07:41,794 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" + "2024-04-08 09:24:22,635 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-05 15:07:41,795 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 2.531621 s\n" + "2024-04-08 09:24:22,636 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 2.490392 s\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-05 15:07:43,580 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" + "2024-04-08 09:24:24,410 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-05 15:07:43,582 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 1.785541 s\n" + "2024-04-08 09:24:24,411 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 1.773785 s\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-05 15:07:44,874 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" + "2024-04-08 09:24:25,651 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-05 15:07:44,875 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 0.162420 s\n" + "2024-04-08 09:24:25,653 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 0.124331 s\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-05 15:07:45,075 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" + "2024-04-08 09:24:25,821 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-05 15:07:45,077 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 0.197449 s\n" + "2024-04-08 09:24:25,822 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 0.163747 s\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-05 15:07:45,168 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" + "2024-04-08 09:24:25,908 \u001b[1;37mINFO\u001b[0m cycquery.orm - Query returned successfully!\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "2024-04-05 15:07:45,170 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 0.091991 s\n" + "2024-04-08 09:24:25,909 \u001b[1;37mINFO\u001b[0m cycquery.utils.profile - Finished executing function run_query in 0.086249 s\n" ] } ], @@ -398,10 +398,10 @@ "id": "c576ee51-e825-4970-86e8-3e5f221f145c", "metadata": { "execution": { - "iopub.execute_input": "2024-04-05T19:07:45.214446Z", - "iopub.status.busy": "2024-04-05T19:07:45.214076Z", - "iopub.status.idle": "2024-04-05T19:07:45.299135Z", - "shell.execute_reply": "2024-04-05T19:07:45.298483Z" + "iopub.execute_input": "2024-04-08T13:24:25.953995Z", + "iopub.status.busy": "2024-04-08T13:24:25.953646Z", + "iopub.status.idle": "2024-04-08T13:24:26.040715Z", + "shell.execute_reply": "2024-04-08T13:24:26.039906Z" }, "tags": [] }, @@ -1497,9 +1497,9 @@ } }, "text/html": [ - "
+ + \ No newline at end of file diff --git a/api/tutorials_use_cases.html b/api/tutorials_use_cases.html index 314f69e29..c5751deb7 100644 --- a/api/tutorials_use_cases.html +++ b/api/tutorials_use_cases.html @@ -558,5 +558,7 @@

NIH Chest X-ray classification + + \ No newline at end of file diff --git a/api/user_guide.html b/api/user_guide.html index 1f0678d4d..0870d13a4 100644 --- a/api/user_guide.html +++ b/api/user_guide.html @@ -414,5 +414,7 @@

User Guide + + \ No newline at end of file diff --git a/assets/js/d098a0ec.101bc726.js b/assets/js/1cd7c442.f735fc16.js similarity index 64% rename from assets/js/d098a0ec.101bc726.js rename to assets/js/1cd7c442.f735fc16.js index b9be944a8..a79b9f9ce 100644 --- a/assets/js/d098a0ec.101bc726.js +++ b/assets/js/1cd7c442.f735fc16.js @@ -1 +1 @@ -"use strict";(self.webpackChunkdocusaurus=self.webpackChunkdocusaurus||[]).push([[963],{3769:u=>{u.exports=JSON.parse('{"name":"docusaurus-plugin-content-docs","id":"default"}')}}]); \ No newline at end of file +"use strict";(self.webpackChunkdocusaurus=self.webpackChunkdocusaurus||[]).push([[305],{3769:u=>{u.exports=JSON.parse('{"name":"docusaurus-plugin-content-docs","id":"default"}')}}]); \ No newline at end of file diff --git a/assets/js/72bee0c1.b6c646b2.js b/assets/js/9f179204.8d399381.js similarity index 64% rename from assets/js/72bee0c1.b6c646b2.js rename to assets/js/9f179204.8d399381.js index a8f1716b1..ece834407 100644 --- a/assets/js/72bee0c1.b6c646b2.js +++ b/assets/js/9f179204.8d399381.js @@ -1 +1 @@ -"use strict";(self.webpackChunkdocusaurus=self.webpackChunkdocusaurus||[]).push([[810],{4469:u=>{u.exports=JSON.parse('{"name":"docusaurus-plugin-content-blog","id":"default"}')}}]); \ No newline at end of file +"use strict";(self.webpackChunkdocusaurus=self.webpackChunkdocusaurus||[]).push([[419],{4469:u=>{u.exports=JSON.parse('{"name":"docusaurus-plugin-content-blog","id":"default"}')}}]); \ No newline at end of file diff --git a/assets/js/3e9d370c.29f4916b.js b/assets/js/b91d99ed.37214bf2.js similarity index 65% rename from assets/js/3e9d370c.29f4916b.js rename to assets/js/b91d99ed.37214bf2.js index f6c10e496..be9a86ac1 100644 --- a/assets/js/3e9d370c.29f4916b.js +++ b/assets/js/b91d99ed.37214bf2.js @@ -1 +1 @@ -"use strict";(self.webpackChunkdocusaurus=self.webpackChunkdocusaurus||[]).push([[301],{5745:u=>{u.exports=JSON.parse('{"name":"docusaurus-plugin-content-pages","id":"default"}')}}]); \ No newline at end of file +"use strict";(self.webpackChunkdocusaurus=self.webpackChunkdocusaurus||[]).push([[349],{5745:u=>{u.exports=JSON.parse('{"name":"docusaurus-plugin-content-pages","id":"default"}')}}]); \ No newline at end of file diff --git a/assets/js/main.068b329c.js b/assets/js/main.068b329c.js new file mode 100644 index 000000000..3f5513707 --- /dev/null +++ b/assets/js/main.068b329c.js @@ -0,0 +1,2 @@ +/*! 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