Merge pull request numenta#262 from zuhaagha/update-sliding-threshold…

…-scores Update sliding threshold scores
ndnchapathi69 · Jul 22, 2016 · 7b15b44 · 7b15b44
2 parents 8bd55fb + e2afd63
commit 7b15b44
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diff --git a/README.md b/README.md
@@ -37,9 +37,9 @@ The NAB scores are normalized such that the maximum possible is 100.0 (i.e. the
 | [Numenta HTM](https://github.com/numenta/nupic)* | 65.3          | 58.6          | 69.4          |
 | [Twitter ADVec v1.0.0](https://github.com/twitter/AnomalyDetection)| 47.1             | 33.6          | 53.5          |
 | [Etsy Skyline](https://github.com/etsy/skyline) | 35.7             | 27.1          | 44.5          |
+| [Sliding Threshold](https://github.com/numenta/NAB/blob/master/nab/detectors/gaussian/windowedGaussian_detector.py) | 30.7             | 12.1         | 38.3          |
 | Bayesian Changepoint**          | 17.7              | 3.2           | 32.2           |
 |  [EXPoSE](https://arxiv.org/abs/1601.06602v3)   | 16.4     | 3.2  | 26.9     |
-| [Sliding Threshold](https://github.com/numenta/NAB/blob/master/nab/detectors/gaussian/windowedGaussian_detector.py) | 15.0             | -26.2          | 30.1          |
 | Random***       | 11.0             | 1.2          | 19.5          |
 | Null          | 0.0              | 0.0           | 0.0           |
 

diff --git a/config/thresholds.json b/config/thresholds.json
@@ -113,16 +113,16 @@
     },
     "windowedGaussian": {
         "reward_low_FN_rate": {
-            "score": -127.16881016907034,
-            "threshold": 0.9999998092651373
+            "score": -98.7538610655,
+            "threshold": 1.0
         },
         "reward_low_FP_rate": {
-            "score": -176.80116502414384,
-            "threshold": 0.9999998092651373
+            "score": -87.9970284629,
+            "threshold": 1.0
         },
         "standard": {
-            "score": -81.16881016907035,
-            "threshold": 0.9999998092651373
+            "score": -44.7538610655,
+            "threshold": 1.0
         }
     }
 }
diff --git a/results/final_results.json b/results/final_results.json
@@ -20,7 +20,7 @@
         "standard": 65.36727069939656
     },
     "numentaTM": {
-        "reward_low_FN_rate": 65.904839452382177,
+        "reward_low_FN_rate": 65.90483945238218,
         "reward_low_FP_rate": 52.366094841866385,
         "standard": 60.926224695818966
     },
@@ -40,8 +40,8 @@
         "standard": 47.06195725408189
     },
     "windowedGaussian": {
-        "reward_low_FN_rate": 30.123905123850577,
-        "reward_low_FP_rate": -26.207398717241393,
-        "standard": 15.013443892629311
+        "reward_low_FN_rate": 38.28912038347701,
+        "reward_low_FP_rate": 12.070246352198273,
+        "standard": 30.70954264418103
     }
 }
diff --git a/...ts/windowedGaussian/artificialWithAnomaly/windowedGaussian_art_increase_spike_density.csv b/...ts/windowedGaussian/artificialWithAnomaly/windowedGaussian_art_increase_spike_density.csv
diff --git a/results/windowedGaussian/artificialWithAnomaly/windowedGaussian_art_load_balancer_spikes.csv b/results/windowedGaussian/artificialWithAnomaly/windowedGaussian_art_load_balancer_spikes.csv
@@ -748,7 +748,7 @@ timestamp,value,anomaly_score,label,S(t)_reward_low_FP_rate,S(t)_reward_low_FN_r
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-2014-04-03 14:25:00,1.6705581002,0.99999999808,0,-0.22,-0.11,-0.11
+2014-04-03 14:25:00,1.6705581002,0.99999999808,0,0.0,0.0,0.0
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@@ -856,7 +856,7 @@ timestamp,value,anomaly_score,label,S(t)_reward_low_FP_rate,S(t)_reward_low_FN_r
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@@ -925,7 +925,7 @@ timestamp,value,anomaly_score,label,S(t)_reward_low_FP_rate,S(t)_reward_low_FN_r
 2014-04-04 04:55:00,0.0,0.419342024499,0,0.0,0.0,0.0
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@@ -1023,7 +1023,7 @@ timestamp,value,anomaly_score,label,S(t)_reward_low_FP_rate,S(t)_reward_low_FN_r
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+2014-04-04 13:20:00,2.0410876746,0.999999987832,0,0.0,0.0,0.0
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@@ -1320,8 +1320,8 @@ timestamp,value,anomaly_score,label,S(t)_reward_low_FP_rate,S(t)_reward_low_FN_r
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@@ -1366,7 +1366,7 @@ timestamp,value,anomaly_score,label,S(t)_reward_low_FP_rate,S(t)_reward_low_FN_r
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@@ -1408,7 +1408,7 @@ timestamp,value,anomaly_score,label,S(t)_reward_low_FP_rate,S(t)_reward_low_FN_r
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@@ -1457,7 +1457,7 @@ timestamp,value,anomaly_score,label,S(t)_reward_low_FP_rate,S(t)_reward_low_FN_r
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@@ -1729,7 +1729,7 @@ timestamp,value,anomaly_score,label,S(t)_reward_low_FP_rate,S(t)_reward_low_FN_r
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@@ -2006,7 +2006,7 @@ timestamp,value,anomaly_score,label,S(t)_reward_low_FP_rate,S(t)_reward_low_FN_r
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@@ -2371,7 +2371,7 @@ timestamp,value,anomaly_score,label,S(t)_reward_low_FP_rate,S(t)_reward_low_FN_r
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@@ -2441,7 +2441,7 @@ timestamp,value,anomaly_score,label,S(t)_reward_low_FP_rate,S(t)_reward_low_FN_r
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@@ -2516,7 +2516,7 @@ timestamp,value,anomaly_score,label,S(t)_reward_low_FP_rate,S(t)_reward_low_FN_r
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@@ -2690,7 +2690,7 @@ timestamp,value,anomaly_score,label,S(t)_reward_low_FP_rate,S(t)_reward_low_FN_r
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@@ -3137,10 +3137,10 @@ timestamp,value,anomaly_score,label,S(t)_reward_low_FP_rate,S(t)_reward_low_FN_r
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@@ -3248,8 +3248,8 @@ timestamp,value,anomaly_score,label,S(t)_reward_low_FP_rate,S(t)_reward_low_FN_r
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@@ -3555,7 +3555,7 @@ timestamp,value,anomaly_score,label,S(t)_reward_low_FP_rate,S(t)_reward_low_FN_r
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@@ -3650,7 +3650,7 @@ timestamp,value,anomaly_score,label,S(t)_reward_low_FP_rate,S(t)_reward_low_FN_r
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 2014-04-13 16:20:00,1.0662669244,0.981950877945,0,0.0,0.0,0.0
 2014-04-13 16:25:00,0.0,0.402846977375,0,0.0,0.0,0.0
 2014-04-13 16:30:00,0.0,0.402860794607,0,0.0,0.0,0.0
@@ -3809,7 +3809,7 @@ timestamp,value,anomaly_score,label,S(t)_reward_low_FP_rate,S(t)_reward_low_FN_r
 2014-04-14 05:15:00,0.0,0.402949573285,0,0.0,0.0,0.0
 2014-04-14 05:20:00,0.0,0.402962816648,0,0.0,0.0,0.0
 2014-04-14 05:25:00,1.2329254978,0.993526452965,0,0.0,0.0,0.0
-2014-04-14 05:30:00,2.7595338758,0.999999997713,0,-0.219899393512,-0.109949696756,-0.109949696756
+2014-04-14 05:30:00,2.7595338758,0.999999997713,0,0.0,0.0,0.0
 2014-04-14 05:35:00,0.0,0.402609677635,0,0.0,0.0,0.0
 2014-04-14 05:40:00,0.0,0.402622956925,0,0.0,0.0,0.0
 2014-04-14 05:45:00,0.0,0.402636230785,0,0.0,0.0,0.0

diff --git a/results/windowedGaussian/realAWSCloudwatch/windowedGaussian_ec2_cpu_utilization_53ea38.csv b/results/windowedGaussian/realAWSCloudwatch/windowedGaussian_ec2_cpu_utilization_53ea38.csv
@@ -734,7 +734,7 @@ timestamp,value,anomaly_score,label,S(t)_reward_low_FP_rate,S(t)_reward_low_FN_r
 2014-02-17 03:30:00,1.868,0.709940271586,0,0.0,0.0,0.0
 2014-02-17 03:35:00,1.758,0.282062066107,0,0.0,0.0,0.0
 2014-02-17 03:40:00,1.976,0.951860652428,0,0.0,0.0,0.0
-2014-02-17 03:45:00,2.432,0.999999999883,0,-0.22,-0.11,-0.11
+2014-02-17 03:45:00,2.432,0.999999999883,0,0.0,0.0,0.0
 2014-02-17 03:50:00,1.8,0.439794869533,0,0.0,0.0,0.0
 2014-02-17 03:55:00,1.832,0.567007155427,0,0.0,0.0,0.0
 2014-02-17 04:00:00,1.83,0.559073199679,0,0.0,0.0,0.0
@@ -1306,7 +1306,7 @@ timestamp,value,anomaly_score,label,S(t)_reward_low_FP_rate,S(t)_reward_low_FN_r
 2014-02-19 03:10:00,2.026,0.983115914819,0,0.0,0.0,0.0
 2014-02-19 03:15:00,1.906,0.814556837935,0,0.0,0.0,0.0
 2014-02-19 03:20:00,1.798,0.417974146324,0,0.0,0.0,0.0
-2014-02-19 03:25:00,2.4,0.99999999852,0,-0.22,-0.11,-0.11
+2014-02-19 03:25:00,2.4,0.99999999852,0,0.0,0.0,0.0
 2014-02-19 03:30:00,1.826,0.529152007776,0,0.0,0.0,0.0
 2014-02-19 03:35:00,1.832,0.553122090671,0,0.0,0.0,0.0
 2014-02-19 03:40:00,1.874,0.711154634186,0,0.0,0.0,0.0
@@ -1882,7 +1882,7 @@ timestamp,value,anomaly_score,label,S(t)_reward_low_FP_rate,S(t)_reward_low_FN_r
 2014-02-21 03:10:00,1.998,0.960464432025,0,0.0,0.0,0.0
 2014-02-21 03:15:00,1.794,0.393204187342,0,0.0,0.0,0.0
 2014-02-21 03:20:00,1.772,0.312295157068,0,0.0,0.0,0.0
-2014-02-21 03:25:00,2.4,0.999999995484,0,-0.219663443913,-0.109831721956,-0.109831721956
+2014-02-21 03:25:00,2.4,0.999999995484,0,0.0,0.0,0.0
 2014-02-21 03:30:00,1.892,0.756064117926,0,0.0,0.0,0.0
 2014-02-21 03:35:00,1.74,0.210772739957,0,0.0,0.0,0.0
 2014-02-21 03:40:00,2.0,0.96060870682,0,0.0,0.0,0.0
@@ -2558,7 +2558,7 @@ timestamp,value,anomaly_score,label,S(t)_reward_low_FP_rate,S(t)_reward_low_FN_r
 2014-02-23 11:30:00,1.826,0.501807155778,0,0.0,0.0,0.0
 2014-02-23 11:35:00,1.738,0.193109665467,0,0.0,0.0,0.0
 2014-02-23 11:40:00,2.0,0.957934297495,0,0.0,0.0,0.0
-2014-02-23 11:45:00,1.734,0.182437370573,1,0.809358444382,0.809358444382,0.809358444382
+2014-02-23 11:45:00,1.734,0.182437370573,1,0.125419508811,0.125419508811,0.125419508811
 2014-02-23 11:50:00,1.8,0.400240698379,1,0.0,0.0,0.0
 2014-02-23 11:55:00,1.732,0.177312983456,1,0.0,0.0,0.0
 2014-02-23 12:00:00,1.894,0.751116502646,1,0.0,0.0,0.0
@@ -3320,7 +3320,7 @@ timestamp,value,anomaly_score,label,S(t)_reward_low_FP_rate,S(t)_reward_low_FN_r
 2014-02-26 03:00:00,1.798,0.378662263807,0,0.0,0.0,0.0
 2014-02-26 03:05:00,1.766,0.267085055053,0,0.0,0.0,0.0
 2014-02-26 03:10:00,1.966,0.908747504608,0,0.0,0.0,0.0
-2014-02-26 03:15:00,2.366,0.999999920266,0,-0.219999651971,-0.109999825986,-0.109999825986
+2014-02-26 03:15:00,2.366,0.999999920266,0,0.0,0.0,0.0
 2014-02-26 03:20:00,1.798,0.378470951234,0,0.0,0.0,0.0
 2014-02-26 03:25:00,1.834,0.51634987155,0,0.0,0.0,0.0
 2014-02-26 03:30:00,1.8,0.385894762571,0,0.0,0.0,0.0
@@ -3608,7 +3608,7 @@ timestamp,value,anomaly_score,label,S(t)_reward_low_FP_rate,S(t)_reward_low_FN_r
 2014-02-27 03:00:00,1.86,0.61753804679,0,0.0,0.0,0.0
 2014-02-27 03:05:00,1.772,0.284762772083,0,0.0,0.0,0.0
 2014-02-27 03:10:00,2.0,0.953498470203,0,0.0,0.0,0.0
-2014-02-27 03:15:00,2.466,0.999999999823,0,-0.22,-0.11,-0.11
+2014-02-27 03:15:00,2.466,0.999999999823,0,0.0,0.0,0.0
 2014-02-27 03:20:00,1.766,0.265480051932,0,0.0,0.0,0.0
 2014-02-27 03:25:00,1.8,0.384778871381,0,0.0,0.0,0.0
 2014-02-27 03:30:00,1.834,0.516192462886,0,0.0,0.0,0.0
@@ -3900,7 +3900,7 @@ timestamp,value,anomaly_score,label,S(t)_reward_low_FP_rate,S(t)_reward_low_FN_r
 2014-02-28 03:20:00,1.798,0.375335634227,0,0.0,0.0,0.0
 2014-02-28 03:25:00,1.804,0.398007389694,0,0.0,0.0,0.0
 2014-02-28 03:30:00,1.828,0.491367993017,0,0.0,0.0,0.0
-2014-02-28 03:35:00,2.488,0.999999999958,0,-0.22,-0.11,-0.11
+2014-02-28 03:35:00,2.488,0.999999999958,0,0.0,0.0,0.0
 2014-02-28 03:40:00,1.942,0.863469931291,0,0.0,0.0,0.0
 2014-02-28 03:45:00,1.734,0.171997616556,0,0.0,0.0,0.0
 2014-02-28 03:50:00,1.798,0.375339436143,0,0.0,0.0,0.0

diff --git a/results/windowedGaussian/realAWSCloudwatch/windowedGaussian_ec2_cpu_utilization_5f5533.csv b/results/windowedGaussian/realAWSCloudwatch/windowedGaussian_ec2_cpu_utilization_5f5533.csv
@@ -2829,7 +2829,7 @@ timestamp,value,anomaly_score,label,S(t)_reward_low_FP_rate,S(t)_reward_low_FN_r
 2014-02-24 10:02:00,44.108,0.408220072349,0,0.0,0.0,0.0
 2014-02-24 10:07:00,45.422,0.552275434945,0,0.0,0.0,0.0
 2014-02-24 10:12:00,43.616,0.356326131608,0,0.0,0.0,0.0
-2014-02-24 10:17:00,42.984,0.293526592427,1,0.64900175643,0.64900175643,0.64900175643
+2014-02-24 10:17:00,42.984,0.293526592427,1,-1.0,-2.0,-1.0
 2014-02-24 10:22:00,40.212,0.095071152515,1,0.0,0.0,0.0
 2014-02-24 10:27:00,47.16,0.730106950234,1,0.0,0.0,0.0
 2014-02-24 10:32:00,43.568,0.351561383566,1,0.0,0.0,0.0