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HelmholtzAI-Consultants-Munich · Sep 18, 2024 · 2b575c4 · 2b575c4
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diff --git a/.../Bio-1-Tutorial_RandomForest_Models.ipynb → ...ial_RandomForest_Model_BreastCancer.ipynb b/.../Bio-1-Tutorial_RandomForest_Models.ipynb → ...ial_RandomForest_Model_BreastCancer.ipynb
diff --git a/...torial_PermutationFeatureImportance.ipynb → ...torial_PermutationFeatureImportance.ipynb b/...torial_PermutationFeatureImportance.ipynb → ...torial_PermutationFeatureImportance.ipynb
@@ -162,7 +162,7 @@
    "id": "50c9a126",
    "metadata": {},
    "source": [
-    "In the notebook [*Bio-1-Tutorial_RandomForest_Models.ipynb*](./Bio-1-Tutorial_RandomForest_Models.ipynb), we explain how to do the exploratory data analysis, preprocess the data and train a Random Forest model with the given data. The focus of this notebook is the interpretation of the previously trained model."
+    "In the notebook [*Bio-0-Tutorial_RandomForest_Model_BreastCancer.ipynb*](./Bio-0-Tutorial_RandomForest_Model_BreastCancer.ipynb), we explain how to do the exploratory data analysis, preprocess the data and train a Random Forest model with the given data. The focus of this notebook is the interpretation of the previously trained model."
    ]
   },
   {

diff --git a/...r-random-forest/Bio-4-Tutorial_SHAP.ipynb → ...r-random-forest/Bio-3-Tutorial_SHAP.ipynb b/...r-random-forest/Bio-4-Tutorial_SHAP.ipynb → ...r-random-forest/Bio-3-Tutorial_SHAP.ipynb
@@ -166,7 +166,7 @@
    "id": "04fa2d65",
    "metadata": {},
    "source": [
-    "In the notebook [*Bio-1-Tutorial_RandomForest_Models.ipynb*](./Bio-1-Tutorial_RandomForest_Models.ipynb), we explain how to do the exploratory data analysis, preprocess the data and train a Random Forest model with the given data. The focus of this notebook is the interpretation of the previously trained model."
+    "In the notebook [*Bio-0-Tutorial_RandomForest_Model_BreastCancer.ipynb*](./Bio-0-Tutorial_RandomForest_Model_BreastCancer.ipynb), we explain how to do the exploratory data analysis, preprocess the data and train a Random Forest model with the given data. The focus of this notebook is the interpretation of the previously trained model."
    ]
   },
   {

diff --git a/...or-random-forest/Bio-5-Tutorial_FGC.ipynb → ...or-random-forest/Bio-4-Tutorial_FGC.ipynb b/...or-random-forest/Bio-5-Tutorial_FGC.ipynb → ...or-random-forest/Bio-4-Tutorial_FGC.ipynb
@@ -163,7 +163,7 @@
    "id": "29de153b",
    "metadata": {},
    "source": [
-    "In the notebook [*Bio-1-Tutorial_RandomForest_Models.ipynb*](./Bio-1-Tutorial_RandomForest_Models.ipynb), we explain how to do the exploratory data analysis, preprocess the data and train a Random Forest model with the given data. The focus of this notebook is the interpretation of the previously trained model."
+    "In the notebook [*Bio-0-Tutorial_RandomForest_Model_BreastCancer.ipynb*](./Bio-0-Tutorial_RandomForest_Model_BreastCancer.ipynb), we explain how to do the exploratory data analysis, preprocess the data and train a Random Forest model with the given data. The focus of this notebook is the interpretation of the previously trained model."
    ]
   },
   {