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diff --git a/docs/evaluation/KShapeAD.csv b/docs/evaluation/KShapeAD.csv
deleted file mode 100644
index e3c77fdd0a2793bac88262dcdea207f377bb7890..0000000000000000000000000000000000000000
--- a/docs/evaluation/KShapeAD.csv
+++ /dev/null
@@ -1,2 +0,0 @@
-params,file_name,duration,group,point anomaly,seq anomaly,AUC-PR,AUC-ROC,VUS-PR,VUS-ROC,Standard-F1,PA-F1,Event-based-F1,R-based-F1,Affiliation-F,Recall,Precision
-{'periodicity': 2},280_NEK_id_4_WebService_tr_500_1st_231.csv,0.9505062103271484,NEK,False,False,0.07926785813478894,0.6630577427821522,0.10358866434207449,0.5544817330166786,0.18676697609674528,0.2742857142857143,0.1660457690260775,0.33959170607433914,0.7497700296391373,0.0,0.0
diff --git a/docs/evaluation/Vergleich der Ergebnisse.md b/docs/evaluation/Vergleich der Ergebnisse.md
index 5e2514568d56870154fd5a757cd3b47254f01744..61212dc3dcce8aa3cbfd47c1de81aeb3a51d0ac0 100644
--- a/docs/evaluation/Vergleich der Ergebnisse.md
+++ b/docs/evaluation/Vergleich der Ergebnisse.md
@@ -3,8 +3,8 @@
| Laufzeiten | POLY | iForest | PCA | USAD | CNN | OmAn | LSTM | kShape | kMeans | OCSVM | LOF | Sub-LOF | KNN |
| ------------------------------ | ---- | ------- | ---- | ---- | ---- | ---- | ---- | ------ | ------ | ----- | ---- | ------- | ---- |
| **Bei Autoren (s)** | 0.09 | 0.14 | 2 | 2 | 3 | 4 | 8 | 8.5 | 20 | 30 | 70 | 80 | 90 |
-| **Insgesamt (h)** | 3.42 | 3.44 | 4.26 | 3.19 | 2.93 | 3.42 | 3.66 | | 5.62 | | 2.04 | | 6.68 |
-| **Durchschnitt pro Datei (s)** | 31.0 | 31.2 | 38.7 | 28.9 | 26.6 | 31 | 33.2 | | 50.9 | | 18.5 | | 60.5 |
+| **Insgesamt (h)** | 3.42 | 3.44 | 4.26 | 3.19 | 2.93 | 3.42 | 3.66 | | 5.62 | | 2.04 | 5.14 | 6.68 |
+| **Durchschnitt pro Datei (s)** | 31.0 | 31.2 | 38.7 | 28.9 | 26.6 | 31 | 33.2 | | 50.9 | | 18.5 | 46.6 | 60.5 |
# Datensätze
+ Gesamtanzahl Zeitserien: 397
@@ -13,138 +13,138 @@
+ Anzahl an Zeitserien mit nur Sequenzanomalien: 158
## Gesamtbewertung nach AUC-PR
-| Datensatz | POLY | iForest | PCA | USAD | CNN | OmAn | LSTM | kShape | kMeans | OCSVM | LOF | Sub-LOF | KNN | Datensatz |
-| ------------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | ------ | --------- | ----- | --------- | ------- | --------- | ------------- |
-| UCR | 0.156850 | 0.059389 | 0.138533 | 0.088392 | 0.069477 | 0.085236 | 0.028041 | | 0.487206 | | 0.048985 | | 0.283830 | UCR |
-| SMD | 0.639394 | 0.369237 | 0.495851 | 0.665737 | 0.565370 | 0.531140 | 0.539890 | | 0.260908 | | 0.182353 | | 0.162970 | SMD |
-| YAHOO | 0.075395 | 0.092730 | 0.117107 | 0.117266 | 0.561562 | 0.148188 | 0.443957 | | 0.699444 | | 0.409909 | | 0.144445 | YAHOO |
-| Exathlon | 0.844513 | 0.962806 | 0.958102 | 0.862358 | 0.654310 | 0.874519 | 0.733875 | | 0.617690 | | 0.245106 | | 0.563481 | Exathlon |
-| NAB | 0.526439 | 0.314587 | 0.486528 | 0.300305 | 0.223347 | 0.332227 | 0.153306 | | 0.401505 | | 0.144844 | | 0.311100 | NAB |
-| OPPORTUNITY | 0.420658 | 0.733153 | 0.923192 | 0.651235 | 0.619160 | 0.649867 | 0.545535 | | 0.365381 | | 0.153396 | | 0.298396 | OPPORTUNITY |
-| WSD | 0.427387 | 0.040993 | 0.216542 | 0.240276 | 0.303128 | 0.251057 | 0.209492 | | 0.146372 | | 0.141918 | | 0.044597 | WSD |
-| SVDB | 0.506002 | 0.311936 | 0.558896 | 0.459209 | 0.197103 | 0.476835 | 0.129879 | | 0.809036 | | 0.044940 | | 0.538270 | SVDB |
-| SMAP | 0.604826 | 0.299302 | 0.484416 | 0.273159 | 0.329931 | 0.385082 | 0.278827 | | 0.648913 | | 0.180797 | | 0.453816 | SMAP |
-| IOPS | 0.332866 | 0.231569 | 0.372849 | 0.403523 | 0.265889 | 0.368163 | 0.320195 | | 0.068715 | | 0.116787 | | 0.070598 | IOPS |
-| TODS | 0.239024 | 0.076521 | 0.124321 | 0.163915 | 0.303786 | 0.172369 | 0.205671 | | 0.448703 | | 0.100820 | | 0.410649 | TODS |
-| Stock | 0.146590 | 0.143940 | 0.148428 | 0.133570 | 0.929344 | 0.133646 | 0.519232 | | 0.114476 | | 0.112061 | | 0.096103 | Stock |
-| MGAB | 0.008996 | 0.004336 | 0.027123 | 0.032097 | 0.003855 | 0.015268 | 0.045860 | | 0.085299 | | 0.002209 | | 0.325650 | MGAB |
-| MSL | 0.629533 | 0.386085 | 0.493320 | 0.267256 | 0.307033 | 0.394283 | 0.237442 | | 0.371438 | | 0.151228 | | 0.313525 | MSL |
-| NEK | 0.709458 | 0.630339 | 0.891733 | 0.816021 | 0.685573 | 0.836145 | 0.667421 | | 0.346973 | | 0.363561 | | 0.119174 | NEK |
-| LTDB | 0.455324 | 0.521341 | 0.489411 | 0.461335 | 0.354462 | 0.479711 | 0.276735 | | 0.765819 | | 0.203241 | | 0.589828 | LTDB |
-| MITDB | 0.366934 | 0.169557 | 0.377853 | 0.201810 | 0.160153 | 0.206999 | 0.113066 | | 0.583808 | | 0.051628 | | 0.500834 | MITDB |
-| TAO | 0.140526 | 0.125817 | 0.149144 | 0.339781 | 0.994857 | 0.344060 | 0.993397 | | 0.129147 | | 0.167995 | | 0.108733 | TAO |
-| SED | 0.031421 | 0.691484 | 0.020994 | 0.026231 | 0.029325 | 0.031663 | 0.030497 | | 0.710575 | | 0.082198 | | 0.707453 | SED |
-| Daphnet | 0.536827 | 0.496579 | 0.468647 | 0.192057 | 0.381499 | 0.192069 | 0.132234 | | 0.036445 | | 0.129509 | | 0.033893 | Daphnet |
-| SWaT | 0.123133 | 0.702432 | 0.756700 | 0.757484 | 0.738718 | 0.757687 | 0.737695 | | 0.111152 | | 0.120683 | | 0.110376 | SWaT |
-| Power | 0.203760 | 0.073981 | 0.078866 | 0.064665 | 0.072400 | 0.064665 | 0.064788 | | 0.507629 | | 0.086245 | | 0.160167 | Power |
-| CATSv2 | 0.476434 | 0.139416 | 0.474705 | 0.481625 | 0.411894 | 0.437868 | 0.358071 | | 0.455611 | | 0.071542 | | 0.482166 | CATSv2 |
-| **Insgesamt** | **0.394** | **0.304** | **0.407** | **0.352** | **0.366** | **0.354** | **0.313** | | **0.444** | | **0.156** | | **0.292** | **Insgesamt** |
+| Datensatz | POLY | iForest | PCA | USAD | CNN | OmAn | LSTM | kShape | kMeans | OCSVM | LOF | Sub-LOF | KNN | Datensatz |
+| ------------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | ------ | --------- | ----- | --------- | --------- | --------- | ------------- |
+| UCR | 0.156850 | 0.059389 | 0.138533 | 0.088392 | 0.069477 | 0.085236 | 0.028041 | | 0.487206 | | 0.048985 | 0.495182 | 0.283830 | UCR |
+| SMD | 0.639394 | 0.369237 | 0.495851 | 0.665737 | 0.565370 | 0.531140 | 0.539890 | | 0.260908 | | 0.182353 | 0.486307 | 0.162970 | SMD |
+| YAHOO | 0.075395 | 0.092730 | 0.117107 | 0.117266 | 0.561562 | 0.148188 | 0.443957 | | 0.699444 | | 0.409909 | 0.150503 | 0.144445 | YAHOO |
+| Exathlon | 0.844513 | 0.962806 | 0.958102 | 0.862358 | 0.654310 | 0.874519 | 0.733875 | | 0.617690 | | 0.245106 | 0.257618 | 0.563481 | Exathlon |
+| NAB | 0.526439 | 0.314587 | 0.486528 | 0.300305 | 0.223347 | 0.332227 | 0.153306 | | 0.401505 | | 0.144844 | 0.495381 | 0.311100 | NAB |
+| OPPORTUNITY | 0.420658 | 0.733153 | 0.923192 | 0.651235 | 0.619160 | 0.649867 | 0.545535 | | 0.365381 | | 0.153396 | 0.158653 | 0.298396 | OPPORTUNITY |
+| WSD | 0.427387 | 0.040993 | 0.216542 | 0.240276 | 0.303128 | 0.251057 | 0.209492 | | 0.146372 | | 0.141918 | 0.539254 | 0.044597 | WSD |
+| SVDB | 0.506002 | 0.311936 | 0.558896 | 0.459209 | 0.197103 | 0.476835 | 0.129879 | | 0.809036 | | 0.044940 | 0.356140 | 0.538270 | SVDB |
+| SMAP | 0.604826 | 0.299302 | 0.484416 | 0.273159 | 0.329931 | 0.385082 | 0.278827 | | 0.648913 | | 0.180797 | 0.510341 | 0.453816 | SMAP |
+| IOPS | 0.332866 | 0.231569 | 0.372849 | 0.403523 | 0.265889 | 0.368163 | 0.320195 | | 0.068715 | | 0.116787 | 0.263492 | 0.070598 | IOPS |
+| TODS | 0.239024 | 0.076521 | 0.124321 | 0.163915 | 0.303786 | 0.172369 | 0.205671 | | 0.448703 | | 0.100820 | 0.166507 | 0.410649 | TODS |
+| Stock | 0.146590 | 0.143940 | 0.148428 | 0.133570 | 0.929344 | 0.133646 | 0.519232 | | 0.114476 | | 0.112061 | 0.115033 | 0.096103 | Stock |
+| MGAB | 0.008996 | 0.004336 | 0.027123 | 0.032097 | 0.003855 | 0.015268 | 0.045860 | | 0.085299 | | 0.002209 | 0.567335 | 0.325650 | MGAB |
+| MSL | 0.629533 | 0.386085 | 0.493320 | 0.267256 | 0.307033 | 0.394283 | 0.237442 | | 0.371438 | | 0.151228 | 0.442670 | 0.313525 | MSL |
+| NEK | 0.709458 | 0.630339 | 0.891733 | 0.816021 | 0.685573 | 0.836145 | 0.667421 | | 0.346973 | | 0.363561 | 0.554506 | 0.119174 | NEK |
+| LTDB | 0.455324 | 0.521341 | 0.489411 | 0.461335 | 0.354462 | 0.479711 | 0.276735 | | 0.765819 | | 0.203241 | 0.333160 | 0.589828 | LTDB |
+| MITDB | 0.366934 | 0.169557 | 0.377853 | 0.201810 | 0.160153 | 0.206999 | 0.113066 | | 0.583808 | | 0.051628 | 0.385195 | 0.500834 | MITDB |
+| TAO | 0.140526 | 0.125817 | 0.149144 | 0.339781 | 0.994857 | 0.344060 | 0.993397 | | 0.129147 | | 0.167995 | 0.139803 | 0.108733 | TAO |
+| SED | 0.031421 | 0.691484 | 0.020994 | 0.026231 | 0.029325 | 0.031663 | 0.030497 | | 0.710575 | | 0.082198 | 0.109660 | 0.707453 | SED |
+| Daphnet | 0.536827 | 0.496579 | 0.468647 | 0.192057 | 0.381499 | 0.192069 | 0.132234 | | 0.036445 | | 0.129509 | 0.252282 | 0.033893 | Daphnet |
+| SWaT | 0.123133 | 0.702432 | 0.756700 | 0.757484 | 0.738718 | 0.757687 | 0.737695 | | 0.111152 | | 0.120683 | 0.113563 | 0.110376 | SWaT |
+| Power | 0.203760 | 0.073981 | 0.078866 | 0.064665 | 0.072400 | 0.064665 | 0.064788 | | 0.507629 | | 0.086245 | 0.175035 | 0.160167 | Power |
+| CATSv2 | 0.476434 | 0.139416 | 0.474705 | 0.481625 | 0.411894 | 0.437868 | 0.358071 | | 0.455611 | | 0.071542 | 0.511976 | 0.482166 | CATSv2 |
+| **Insgesamt** | **0.394** | **0.304** | **0.407** | **0.352** | **0.366** | **0.354** | **0.313** | | **0.444** | | **0.156** | **0.374** | **0.292** | **Insgesamt** |
## Gesamtbewertung nach VUS-PR
-| Datensatz | POLY | iForest | PCA | USAD | CNN | OmAn | LSTM | kShape | kMeans | OCSVM | LOF | Sub-LOF | KNN | Datensatz |
-| ------------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | ------ | --------- | ----- | --------- | ------- | --------- | ------------- |
-| UCR | 0.198780 | 0.058773 | 0.152678 | 0.084437 | 0.065443 | 0.089552 | 0.023293 | | 0.486822 | | 0.051489 | | 0.329748 | UCR |
-| SMD | 0.663191 | 0.342406 | 0.467257 | 0.629404 | 0.545045 | 0.478742 | 0.483944 | | 0.254537 | | 0.134985 | | 0.163803 | SMD |
-| YAHOO | 0.307653 | 0.135664 | 0.163729 | 0.192366 | 0.512096 | 0.219787 | 0.417416 | | 0.781824 | | 0.381508 | | 0.502031 | YAHOO |
-| Exathlon | 0.847945 | 0.964836 | 0.959173 | 0.864301 | 0.657757 | 0.876372 | 0.735253 | | 0.618051 | | 0.240338 | | 0.562449 | Exathlon |
-| NAB | 0.584112 | 0.342137 | 0.511398 | 0.308303 | 0.248091 | 0.342007 | 0.173732 | | 0.427477 | | 0.165966 | | 0.341432 | NAB |
-| OPPORTUNITY | 0.426326 | 0.736264 | 0.924516 | 0.651269 | 0.632799 | 0.649931 | 0.563772 | | 0.351828 | | 0.159200 | | 0.295398 | OPPORTUNITY |
-| WSD | 0.531110 | 0.027487 | 0.155366 | 0.155950 | 0.224922 | 0.157612 | 0.130270 | | 0.173060 | | 0.102346 | | 0.083204 | WSD |
-| SVDB | 0.445531 | 0.307322 | 0.523984 | 0.435722 | 0.199785 | 0.445289 | 0.127489 | | 0.811385 | | 0.050189 | | 0.591484 | SVDB |
-| SMAP | 0.727079 | 0.327727 | 0.566842 | 0.302212 | 0.336818 | 0.417852 | 0.273214 | | 0.657738 | | 0.172499 | | 0.558287 | SMAP |
-| IOPS | 0.365055 | 0.134518 | 0.260372 | 0.192815 | 0.205826 | 0.192837 | 0.213044 | | 0.107988 | | 0.123657 | | 0.116527 | IOPS |
-| TODS | 0.586493 | 0.487386 | 0.552877 | 0.529843 | 0.575941 | 0.538194 | 0.522228 | | 0.739257 | | 0.485079 | | 0.780280 | TODS |
-| Stock | 0.805375 | 0.735886 | 0.825382 | 0.771612 | 0.939925 | 0.771658 | 0.817960 | | 0.738198 | | 0.710487 | | 0.691512 | Stock |
-| MGAB | 0.008269 | 0.004379 | 0.005551 | 0.005403 | 0.006988 | 0.005586 | 0.025419 | | 0.036645 | | 0.004639 | | 0.238613 | MGAB |
-| MSL | 0.734244 | 0.448709 | 0.523310 | 0.295208 | 0.346350 | 0.428048 | 0.305128 | | 0.441543 | | 0.186700 | | 0.368746 | MSL |
-| NEK | 0.764836 | 0.649735 | 0.929171 | 0.827283 | 0.714845 | 0.858349 | 0.689697 | | 0.317927 | | 0.395130 | | 0.132908 | NEK |
-| LTDB | 0.510507 | 0.566359 | 0.534873 | 0.512266 | 0.406171 | 0.524763 | 0.329828 | | 0.835553 | | 0.256447 | | 0.692355 | LTDB |
-| MITDB | 0.320425 | 0.159042 | 0.323526 | 0.158357 | 0.143632 | 0.163465 | 0.112398 | | 0.590892 | | 0.053749 | | 0.548995 | MITDB |
-| TAO | 0.808453 | 0.728970 | 0.840276 | 0.928987 | 0.994270 | 0.930020 | 0.995044 | | 0.747945 | | 0.710584 | | 0.684119 | TAO |
-| SED | 0.040176 | 0.807209 | 0.030270 | 0.053374 | 0.058416 | 0.055985 | 0.056562 | | 0.895291 | | 0.111105 | | 0.882987 | SED |
-| Daphnet | 0.519516 | 0.518905 | 0.441568 | 0.122992 | 0.398456 | 0.123026 | 0.133080 | | 0.039747 | | 0.134804 | | 0.035185 | Daphnet |
-| SWaT | 0.103364 | 0.368230 | 0.375512 | 0.365922 | 0.680748 | 0.366250 | 0.669824 | | 0.111519 | | 0.121168 | | 0.110850 | SWaT |
-| Power | 0.122294 | 0.076373 | 0.079616 | 0.067090 | 0.075487 | 0.067090 | 0.067250 | | 0.524166 | | 0.090503 | | 0.166562 | Power |
-| CATSv2 | 0.232252 | 0.105175 | 0.232417 | 0.406831 | 0.288293 | 0.282282 | 0.329056 | | 0.229268 | | 0.063826 | | 0.354730 | CATSv2 |
-| **Insgesamt** | **0.478** | **0.341** | **0.444** | **0.375** | **0.367** | **0.377** | **0.320** | | **0.489** | | **0.185** | | **0.384** | **Insgesamt** |
+| Datensatz | POLY | iForest | PCA | USAD | CNN | OmAn | LSTM | kShape | kMeans | OCSVM | LOF | Sub-LOF | KNN | Datensatz |
+| ------------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | ------ | --------- | ----- | --------- | --------- | --------- | ------------- |
+| UCR | 0.198780 | 0.058773 | 0.152678 | 0.084437 | 0.065443 | 0.089552 | 0.023293 | | 0.486822 | | 0.051489 | 0.514326 | 0.329748 | UCR |
+| SMD | 0.663191 | 0.342406 | 0.467257 | 0.629404 | 0.545045 | 0.478742 | 0.483944 | | 0.254537 | | 0.134985 | 0.544696 | 0.163803 | SMD |
+| YAHOO | 0.307653 | 0.135664 | 0.163729 | 0.192366 | 0.512096 | 0.219787 | 0.417416 | | 0.781824 | | 0.381508 | 0.451001 | 0.502031 | YAHOO |
+| Exathlon | 0.847945 | 0.964836 | 0.959173 | 0.864301 | 0.657757 | 0.876372 | 0.735253 | | 0.618051 | | 0.240338 | 0.262478 | 0.562449 | Exathlon |
+| NAB | 0.584112 | 0.342137 | 0.511398 | 0.308303 | 0.248091 | 0.342007 | 0.173732 | | 0.427477 | | 0.165966 | 0.532450 | 0.341432 | NAB |
+| OPPORTUNITY | 0.426326 | 0.736264 | 0.924516 | 0.651269 | 0.632799 | 0.649931 | 0.563772 | | 0.351828 | | 0.159200 | 0.149548 | 0.295398 | OPPORTUNITY |
+| WSD | 0.531110 | 0.027487 | 0.155366 | 0.155950 | 0.224922 | 0.157612 | 0.130270 | | 0.173060 | | 0.102346 | 0.551041 | 0.083204 | WSD |
+| SVDB | 0.445531 | 0.307322 | 0.523984 | 0.435722 | 0.199785 | 0.445289 | 0.127489 | | 0.811385 | | 0.050189 | 0.383000 | 0.591484 | SVDB |
+| SMAP | 0.727079 | 0.327727 | 0.566842 | 0.302212 | 0.336818 | 0.417852 | 0.273214 | | 0.657738 | | 0.172499 | 0.597854 | 0.558287 | SMAP |
+| IOPS | 0.365055 | 0.134518 | 0.260372 | 0.192815 | 0.205826 | 0.192837 | 0.213044 | | 0.107988 | | 0.123657 | 0.380817 | 0.116527 | IOPS |
+| TODS | 0.586493 | 0.487386 | 0.552877 | 0.529843 | 0.575941 | 0.538194 | 0.522228 | | 0.739257 | | 0.485079 | 0.691125 | 0.780280 | TODS |
+| Stock | 0.805375 | 0.735886 | 0.825382 | 0.771612 | 0.939925 | 0.771658 | 0.817960 | | 0.738198 | | 0.710487 | 0.747567 | 0.691512 | Stock |
+| MGAB | 0.008269 | 0.004379 | 0.005551 | 0.005403 | 0.006988 | 0.005586 | 0.025419 | | 0.036645 | | 0.004639 | 0.634748 | 0.238613 | MGAB |
+| MSL | 0.734244 | 0.448709 | 0.523310 | 0.295208 | 0.346350 | 0.428048 | 0.305128 | | 0.441543 | | 0.186700 | 0.544711 | 0.368746 | MSL |
+| NEK | 0.764836 | 0.649735 | 0.929171 | 0.827283 | 0.714845 | 0.858349 | 0.689697 | | 0.317927 | | 0.395130 | 0.687020 | 0.132908 | NEK |
+| LTDB | 0.510507 | 0.566359 | 0.534873 | 0.512266 | 0.406171 | 0.524763 | 0.329828 | | 0.835553 | | 0.256447 | 0.409530 | 0.692355 | LTDB |
+| MITDB | 0.320425 | 0.159042 | 0.323526 | 0.158357 | 0.143632 | 0.163465 | 0.112398 | | 0.590892 | | 0.053749 | 0.367125 | 0.548995 | MITDB |
+| TAO | 0.808453 | 0.728970 | 0.840276 | 0.928987 | 0.994270 | 0.930020 | 0.995044 | | 0.747945 | | 0.710584 | 0.807694 | 0.684119 | TAO |
+| SED | 0.040176 | 0.807209 | 0.030270 | 0.053374 | 0.058416 | 0.055985 | 0.056562 | | 0.895291 | | 0.111105 | 0.253420 | 0.882987 | SED |
+| Daphnet | 0.519516 | 0.518905 | 0.441568 | 0.122992 | 0.398456 | 0.123026 | 0.133080 | | 0.039747 | | 0.134804 | 0.253956 | 0.035185 | Daphnet |
+| SWaT | 0.103364 | 0.368230 | 0.375512 | 0.365922 | 0.680748 | 0.366250 | 0.669824 | | 0.111519 | | 0.121168 | 0.113915 | 0.110850 | SWaT |
+| Power | 0.122294 | 0.076373 | 0.079616 | 0.067090 | 0.075487 | 0.067090 | 0.067250 | | 0.524166 | | 0.090503 | 0.160858 | 0.166562 | Power |
+| CATSv2 | 0.232252 | 0.105175 | 0.232417 | 0.406831 | 0.288293 | 0.282282 | 0.329056 | | 0.229268 | | 0.063826 | 0.393045 | 0.354730 | CATSv2 |
+| **Insgesamt** | **0.478** | **0.341** | **0.444** | **0.375** | **0.367** | **0.377** | **0.320** | | **0.489** | | **0.185** | **0.473** | **0.384** | **Insgesamt** |
## Gesamtbewertung der Punktanomalien nach AUC-PR
-| Datensatz | POLY | iForest | PCA | USAD | CNN | OmAn | LSTM | kShape | kMeans | OCSVM | LOF | Sub-LOF | KNN | Datensatz |
-| ------------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | ------ | --------- | ----- | --------- | ------- | --------- | ------------- |
-| UCR | 0.000257 | 0.000139 | 0.000196 | 0.000178 | 0.000498 | 0.000178 | 0.000221 | | 0.002843 | | 0.000653 | | 0.003749 | UCR |
-| YAHOO | 0.024161 | 0.007312 | 0.060498 | 0.087663 | 0.587049 | 0.122574 | 0.455103 | | 0.742578 | | 0.422520 | | 0.130716 | YAHOO |
-| WSD | 0.167066 | 0.000501 | 0.206655 | 0.285712 | 0.342989 | 0.407280 | 0.334638 | | 0.003073 | | 0.003879 | | 0.000945 | WSD |
-| IOPS | 0.141657 | 0.011860 | 0.036186 | 0.016979 | 0.210157 | 0.016952 | 0.197084 | | 0.066886 | | 0.176712 | | 0.041389 | IOPS |
-| TODS | 0.061866 | 0.069264 | 0.067229 | 0.065809 | 0.531847 | 0.064650 | 0.367334 | | 0.083989 | | 0.071959 | | 0.075986 | TODS |
-| Stock | 0.146590 | 0.143940 | 0.148428 | 0.133570 | 0.929344 | 0.133646 | 0.519232 | | 0.114476 | | 0.112061 | | 0.096103 | Stock |
-| TAO | 0.148356 | 0.126763 | 0.160428 | 0.330086 | 0.993457 | 0.336829 | 0.994218 | | 0.121904 | | 0.128972 | | 0.098915 | TAO |
-| **Insgesamt** | **0.060** | **0.039** | **0.079** | **0.100** | **0.585** | **0.125** | **0.426** | | **0.451** | | **0.274** | | **0.101** | **Insgesamt** |
+| Datensatz | POLY | iForest | PCA | USAD | CNN | OmAn | LSTM | kShape | kMeans | OCSVM | LOF | Sub-LOF | KNN | Datensatz |
+| ------------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | ------ | --------- | ----- | --------- | --------- | --------- | ------------- |
+| UCR | 0.000257 | 0.000139 | 0.000196 | 0.000178 | 0.000498 | 0.000178 | 0.000221 | | 0.002843 | | 0.000653 | 0.040927 | 0.003749 | UCR |
+| YAHOO | 0.024161 | 0.007312 | 0.060498 | 0.087663 | 0.587049 | 0.122574 | 0.455103 | | 0.742578 | | 0.422520 | 0.141987 | 0.130716 | YAHOO |
+| WSD | 0.167066 | 0.000501 | 0.206655 | 0.285712 | 0.342989 | 0.407280 | 0.334638 | | 0.003073 | | 0.003879 | 0.327958 | 0.000945 | WSD |
+| IOPS | 0.141657 | 0.011860 | 0.036186 | 0.016979 | 0.210157 | 0.016952 | 0.197084 | | 0.066886 | | 0.176712 | 0.121683 | 0.041389 | IOPS |
+| TODS | 0.061866 | 0.069264 | 0.067229 | 0.065809 | 0.531847 | 0.064650 | 0.367334 | | 0.083989 | | 0.071959 | 0.077775 | 0.075986 | TODS |
+| Stock | 0.146590 | 0.143940 | 0.148428 | 0.133570 | 0.929344 | 0.133646 | 0.519232 | | 0.114476 | | 0.112061 | 0.115033 | 0.096103 | Stock |
+| TAO | 0.148356 | 0.126763 | 0.160428 | 0.330086 | 0.993457 | 0.336829 | 0.994218 | | 0.121904 | | 0.128972 | 0.145212 | 0.098915 | TAO |
+| **Insgesamt** | **0.060** | **0.039** | **0.079** | **0.100** | **0.585** | **0.125** | **0.426** | | **0.451** | | **0.274** | **0.131** | **0.101** | **Insgesamt** |
## Gesamtbewertung der Punktanomalien nach VUS-PR
-| Datensatz | POLY | iForest | PCA | USAD | CNN | OmAn | LSTM | kShape | kMeans | OCSVM | LOF | Sub-LOF | KNN | Datensatz |
-| ------------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | ------ | --------- | ----- | --------- | ------- | --------- | ------------- |
-| UCR | 0.003356 | 0.000267 | 0.000408 | 0.000406 | 0.128496 | 0.000406 | 0.000237 | | 0.012483 | | 0.012963 | | 0.011814 | UCR |
-| YAHOO | 0.282071 | 0.052201 | 0.113436 | 0.159136 | 0.519819 | 0.190097 | 0.414255 | | 0.826036 | | 0.383203 | | 0.521624 | YAHOO |
-| WSD | 0.216267 | 0.001036 | 0.124850 | 0.088179 | 0.131018 | 0.105822 | 0.100076 | | 0.021818 | | 0.035113 | | 0.007947 | WSD |
-| IOPS | 0.187766 | 0.017686 | 0.048169 | 0.042432 | 0.147113 | 0.035031 | 0.080739 | | 0.202456 | | 0.073159 | | 0.327373 | IOPS |
-| TODS | 0.803771 | 0.815915 | 0.820717 | 0.780347 | 0.895740 | 0.800324 | 0.852834 | | 0.857103 | | 0.786747 | | 0.855125 | TODS |
-| Stock | 0.805375 | 0.735886 | 0.825382 | 0.771612 | 0.939925 | 0.771658 | 0.817960 | | 0.738198 | | 0.710487 | | 0.691512 | Stock |
-| TAO | 0.761585 | 0.654975 | 0.805852 | 0.907035 | 0.991524 | 0.908594 | 0.992980 | | 0.666432 | | 0.623702 | | 0.570248 | TAO |
-| **Insgesamt** | **0.392** | **0.232** | **0.294** | **0.310** | **0.571** | **0.329** | **0.471** | | **0.680** | | **0.416** | | **0.500** | **Insgesamt** |
+| Datensatz | POLY | iForest | PCA | USAD | CNN | OmAn | LSTM | kShape | kMeans | OCSVM | LOF | Sub-LOF | KNN | Datensatz |
+| ------------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | ------ | --------- | ----- | --------- | --------- | --------- | ------------- |
+| UCR | 0.003356 | 0.000267 | 0.000408 | 0.000406 | 0.128496 | 0.000406 | 0.000237 | | 0.012483 | | 0.012963 | 0.208122 | 0.011814 | UCR |
+| YAHOO | 0.282071 | 0.052201 | 0.113436 | 0.159136 | 0.519819 | 0.190097 | 0.414255 | | 0.826036 | | 0.383203 | 0.475296 | 0.521624 | YAHOO |
+| WSD | 0.216267 | 0.001036 | 0.124850 | 0.088179 | 0.131018 | 0.105822 | 0.100076 | | 0.021818 | | 0.035113 | 0.140331 | 0.007947 | WSD |
+| IOPS | 0.187766 | 0.017686 | 0.048169 | 0.042432 | 0.147113 | 0.035031 | 0.080739 | | 0.202456 | | 0.073159 | 0.327754 | 0.327373 | IOPS |
+| TODS | 0.803771 | 0.815915 | 0.820717 | 0.780347 | 0.895740 | 0.800324 | 0.852834 | | 0.857103 | | 0.786747 | 0.849582 | 0.855125 | TODS |
+| Stock | 0.805375 | 0.735886 | 0.825382 | 0.771612 | 0.939925 | 0.771658 | 0.817960 | | 0.738198 | | 0.710487 | 0.747567 | 0.691512 | Stock |
+| TAO | 0.761585 | 0.654975 | 0.805852 | 0.907035 | 0.991524 | 0.908594 | 0.992980 | | 0.666432 | | 0.623702 | 0.755775 | 0.570248 | TAO |
+| **Insgesamt** | **0.392** | **0.232** | **0.294** | **0.310** | **0.571** | **0.329** | **0.471** | | **0.680** | | **0.416** | **0.514** | **0.500** | **Insgesamt** |
## Gesamtbewertung der Sequenzanomalien nach AUC-PR
-| Datensatz | POLY | iForest | PCA | USAD | CNN | OmAn | LSTM | kShape | kMeans | OCSVM | LOF | Sub-LOF | KNN | Datensatz |
-| ------------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | ------ | --------- | ----- | --------- | ------- | --------- | ------------- |
-| SMD | 0.439343 | 0.336128 | 0.459753 | 0.561216 | 0.505749 | 0.460181 | 0.495482 | | 0.095816 | | 0.163313 | | 0.050501 | SMD |
-| YAHOO | 0.571428 | 0.981990 | 0.690088 | 0.349449 | 0.345384 | 0.349465 | 0.344485 | | 0.462352 | | 0.316546 | | 0.306868 | YAHOO |
-| Exathlon | 0.844513 | 0.962806 | 0.958102 | 0.862358 | 0.654310 | 0.874519 | 0.733875 | | 0.617690 | | 0.245106 | | 0.563481 | Exathlon |
-| NAB | 0.402974 | 0.251317 | 0.439685 | 0.272908 | 0.209869 | 0.335713 | 0.162982 | | 0.230029 | | 0.154619 | | 0.176029 | NAB |
-| OPPORTUNITY | 0.624496 | 0.870159 | 0.968964 | 0.661820 | 0.727956 | 0.661818 | 0.547465 | | 0.276125 | | 0.144952 | | 0.263868 | OPPORTUNITY |
-| WSD | 0.324235 | 0.067695 | 0.099717 | 0.122887 | 0.242314 | 0.123481 | 0.127908 | | 0.253831 | | 0.094898 | | 0.077550 | WSD |
-| SVDB | 0.483934 | 0.313933 | 0.541451 | 0.445765 | 0.198720 | 0.465020 | 0.130291 | | 0.799099 | | 0.046729 | | 0.519348 | SVDB |
-| SMAP | 0.798189 | 0.481811 | 0.887517 | 0.865663 | 0.241609 | 0.876352 | 0.233398 | | 0.928300 | | 0.060424 | | 0.788114 | SMAP |
-| IOPS | 0.482294 | 0.276687 | 0.549216 | 0.710230 | 0.429909 | 0.721261 | 0.461068 | | 0.061431 | | 0.272670 | | 0.031872 | IOPS |
-| TODS | 0.281649 | 0.071679 | 0.149989 | 0.184682 | 0.206602 | 0.191109 | 0.170148 | | 0.592072 | | 0.081599 | | 0.533591 | TODS |
-| MGAB | 0.008996 | 0.004336 | 0.027123 | 0.032097 | 0.003855 | 0.015268 | 0.045860 | | 0.085299 | | 0.002209 | | 0.325650 | MGAB |
-| MSL | 0.557113 | 0.453614 | 0.475464 | 0.104606 | 0.264200 | 0.364941 | 0.257571 | | 0.288743 | | 0.277979 | | 0.238423 | MSL |
-| NEK | 0.568731 | 0.688168 | 0.849600 | 0.863096 | 0.715902 | 0.877024 | 0.681103 | | 0.331911 | | 0.356301 | | 0.146699 | NEK |
-| LTDB | 0.455324 | 0.521341 | 0.489411 | 0.461335 | 0.354462 | 0.479711 | 0.276735 | | 0.765819 | | 0.203241 | | 0.589828 | LTDB |
-| MITDB | 0.366934 | 0.169557 | 0.377853 | 0.201810 | 0.160153 | 0.206999 | 0.113066 | | 0.583808 | | 0.051628 | | 0.500834 | MITDB |
-| SED | 0.031421 | 0.691484 | 0.020994 | 0.026231 | 0.029325 | 0.031663 | 0.030497 | | 0.710575 | | 0.082198 | | 0.707453 | SED |
-| Daphnet | 0.536827 | 0.496579 | 0.468647 | 0.192057 | 0.381499 | 0.192069 | 0.132234 | | 0.036445 | | 0.129509 | | 0.033893 | Daphnet |
-| SWaT | 0.123133 | 0.702432 | 0.756700 | 0.757484 | 0.738718 | 0.757687 | 0.737695 | | 0.111152 | | 0.120683 | | 0.110376 | SWaT |
-| Power | 0.203760 | 0.073981 | 0.078866 | 0.064665 | 0.072400 | 0.064665 | 0.064788 | | 0.507629 | | 0.086245 | | 0.160167 | Power |
-| CATSv2 | 0.476434 | 0.139416 | 0.474705 | 0.481625 | 0.411894 | 0.437868 | 0.358071 | | 0.455611 | | 0.071542 | | 0.482166 | CATSv2 |
-| **Insgesamt** | **0.499** | **0.479** | **0.553** | **0.474** | **0.387** | **0.481** | **0.357** | | **0.449** | | **0.150** | | **0.364** | **Insgesamt** |
+| Datensatz | POLY | iForest | PCA | USAD | CNN | OmAn | LSTM | kShape | kMeans | OCSVM | LOF | Sub-LOF | KNN | Datensatz |
+| ------------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | ------ | --------- | ----- | --------- | --------- | --------- | ------------- |
+| SMD | 0.439343 | 0.336128 | 0.459753 | 0.561216 | 0.505749 | 0.460181 | 0.495482 | | 0.095816 | | 0.163313 | 0.339639 | 0.050501 | SMD |
+| YAHOO | 0.571428 | 0.981990 | 0.690088 | 0.349449 | 0.345384 | 0.349465 | 0.344485 | | 0.462352 | | 0.316546 | 0.242005 | 0.306868 | YAHOO |
+| Exathlon | 0.844513 | 0.962806 | 0.958102 | 0.862358 | 0.654310 | 0.874519 | 0.733875 | | 0.617690 | | 0.245106 | 0.257618 | 0.563481 | Exathlon |
+| NAB | 0.402974 | 0.251317 | 0.439685 | 0.272908 | 0.209869 | 0.335713 | 0.162982 | | 0.230029 | | 0.154619 | 0.457316 | 0.176029 | NAB |
+| OPPORTUNITY | 0.624496 | 0.870159 | 0.968964 | 0.661820 | 0.727956 | 0.661818 | 0.547465 | | 0.276125 | | 0.144952 | 0.154555 | 0.263868 | OPPORTUNITY |
+| WSD | 0.324235 | 0.067695 | 0.099717 | 0.122887 | 0.242314 | 0.123481 | 0.127908 | | 0.253831 | | 0.094898 | 0.452830 | 0.077550 | WSD |
+| SVDB | 0.483934 | 0.313933 | 0.541451 | 0.445765 | 0.198720 | 0.465020 | 0.130291 | | 0.799099 | | 0.046729 | 0.329395 | 0.519348 | SVDB |
+| SMAP | 0.798189 | 0.481811 | 0.887517 | 0.865663 | 0.241609 | 0.876352 | 0.233398 | | 0.928300 | | 0.060424 | 0.488277 | 0.788114 | SMAP |
+| IOPS | 0.482294 | 0.276687 | 0.549216 | 0.710230 | 0.429909 | 0.721261 | 0.461068 | | 0.061431 | | 0.272670 | 0.157124 | 0.031872 | IOPS |
+| TODS | 0.281649 | 0.071679 | 0.149989 | 0.184682 | 0.206602 | 0.191109 | 0.170148 | | 0.592072 | | 0.081599 | 0.240756 | 0.533591 | TODS |
+| MGAB | 0.008996 | 0.004336 | 0.027123 | 0.032097 | 0.003855 | 0.015268 | 0.045860 | | 0.085299 | | 0.002209 | 0.567335 | 0.325650 | MGAB |
+| MSL | 0.557113 | 0.453614 | 0.475464 | 0.104606 | 0.264200 | 0.364941 | 0.257571 | | 0.288743 | | 0.277979 | 0.368527 | 0.238423 | MSL |
+| NEK | 0.568731 | 0.688168 | 0.849600 | 0.863096 | 0.715902 | 0.877024 | 0.681103 | | 0.331911 | | 0.356301 | 0.433487 | 0.146699 | NEK |
+| LTDB | 0.455324 | 0.521341 | 0.489411 | 0.461335 | 0.354462 | 0.479711 | 0.276735 | | 0.765819 | | 0.203241 | 0.333160 | 0.589828 | LTDB |
+| MITDB | 0.366934 | 0.169557 | 0.377853 | 0.201810 | 0.160153 | 0.206999 | 0.113066 | | 0.583808 | | 0.051628 | 0.385195 | 0.500834 | MITDB |
+| SED | 0.031421 | 0.691484 | 0.020994 | 0.026231 | 0.029325 | 0.031663 | 0.030497 | | 0.710575 | | 0.082198 | 0.109660 | 0.707453 | SED |
+| Daphnet | 0.536827 | 0.496579 | 0.468647 | 0.192057 | 0.381499 | 0.192069 | 0.132234 | | 0.036445 | | 0.129509 | 0.252282 | 0.033893 | Daphnet |
+| SWaT | 0.123133 | 0.702432 | 0.756700 | 0.757484 | 0.738718 | 0.757687 | 0.737695 | | 0.111152 | | 0.120683 | 0.113563 | 0.110376 | SWaT |
+| Power | 0.203760 | 0.073981 | 0.078866 | 0.064665 | 0.072400 | 0.064665 | 0.064788 | | 0.507629 | | 0.086245 | 0.175035 | 0.160167 | Power |
+| CATSv2 | 0.476434 | 0.139416 | 0.474705 | 0.481625 | 0.411894 | 0.437868 | 0.358071 | | 0.455611 | | 0.071542 | 0.511976 | 0.482166 | CATSv2 |
+| **Insgesamt** | **0.499** | **0.479** | **0.553** | **0.474** | **0.387** | **0.481** | **0.357** | | **0.449** | | **0.150** | **0.330** | **0.364** | **Insgesamt** |
## Gesamtbewertung der Sequenzanomalien nach VUS-PR
-| Datensatz | POLY | iForest | PCA | USAD | CNN | OmAn | LSTM | kShape | kMeans | OCSVM | LOF | Sub-LOF | KNN | Datensatz |
-| ------------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | ------ | --------- | ----- | --------- | ------- | --------- | ------------- |
-| SMD | 0.482296 | 0.322146 | 0.423162 | 0.519965 | 0.503535 | 0.410939 | 0.453416 | | 0.092843 | | 0.137760 | | 0.063644 | SMD |
-| YAHOO | 0.518566 | 0.936245 | 0.568333 | 0.354527 | 0.351064 | 0.354507 | 0.348855 | | 0.477510 | | 0.304093 | | 0.322916 | YAHOO |
-| Exathlon | 0.847945 | 0.964836 | 0.959173 | 0.864301 | 0.657757 | 0.876372 | 0.735253 | | 0.618051 | | 0.240338 | | 0.562449 | Exathlon |
-| NAB | 0.478372 | 0.285635 | 0.474780 | 0.262268 | 0.238264 | 0.326918 | 0.181686 | | 0.272775 | | 0.183564 | | 0.219327 | NAB |
-| OPPORTUNITY | 0.630618 | 0.868003 | 0.966351 | 0.660160 | 0.741769 | 0.660151 | 0.567052 | | 0.255118 | | 0.152842 | | 0.257788 | OPPORTUNITY |
-| WSD | 0.457794 | 0.038526 | 0.067564 | 0.086910 | 0.206990 | 0.087346 | 0.100554 | | 0.293116 | | 0.073377 | | 0.142998 | WSD |
-| SVDB | 0.423050 | 0.314567 | 0.508621 | 0.424770 | 0.206479 | 0.436465 | 0.131672 | | 0.804472 | | 0.052218 | | 0.579059 | SVDB |
-| SMAP | 0.891481 | 0.487664 | 0.951739 | 0.947702 | 0.237156 | 0.951635 | 0.223192 | | 0.946525 | | 0.046142 | | 0.818737 | SMAP |
-| IOPS | 0.426245 | 0.267117 | 0.422834 | 0.341683 | 0.312286 | 0.380533 | 0.334417 | | 0.112229 | | 0.302989 | | 0.111561 | IOPS |
-| TODS | 0.437694 | 0.174752 | 0.342464 | 0.336685 | 0.331028 | 0.338275 | 0.263210 | | 0.689051 | | 0.198760 | | 0.773793 | TODS |
-| MGAB | 0.008269 | 0.004379 | 0.005551 | 0.005403 | 0.006988 | 0.005586 | 0.025419 | | 0.036645 | | 0.004639 | | 0.238613 | MGAB |
-| MSL | 0.653967 | 0.514630 | 0.492975 | 0.142125 | 0.326973 | 0.412021 | 0.309296 | | 0.405174 | | 0.327778 | | 0.303536 | MSL |
-| NEK | 0.628709 | 0.678337 | 0.880822 | 0.868114 | 0.756555 | 0.884225 | 0.704672 | | 0.298379 | | 0.392335 | | 0.162564 | NEK |
-| LTDB | 0.510507 | 0.566359 | 0.534873 | 0.512266 | 0.406171 | 0.524763 | 0.329828 | | 0.835553 | | 0.256447 | | 0.692355 | LTDB |
-| MITDB | 0.320425 | 0.159042 | 0.323526 | 0.158357 | 0.143632 | 0.163465 | 0.112398 | | 0.590892 | | 0.053749 | | 0.548995 | MITDB |
-| SED | 0.040176 | 0.807209 | 0.030270 | 0.053374 | 0.058416 | 0.055985 | 0.056562 | | 0.895291 | | 0.111105 | | 0.882987 | SED |
-| Daphnet | 0.519516 | 0.518905 | 0.441568 | 0.122992 | 0.398456 | 0.123026 | 0.133080 | | 0.039747 | | 0.134804 | | 0.035185 | Daphnet |
-| SWaT | 0.103364 | 0.368230 | 0.375512 | 0.365922 | 0.680748 | 0.366250 | 0.669824 | | 0.111519 | | 0.121168 | | 0.110850 | SWaT |
-| Power | 0.122294 | 0.076373 | 0.079616 | 0.067090 | 0.075487 | 0.067090 | 0.067250 | | 0.524166 | | 0.090503 | | 0.166562 | Power |
-| CATSv2 | 0.232252 | 0.105175 | 0.232417 | 0.406831 | 0.288293 | 0.282282 | 0.329056 | | 0.229268 | | 0.063826 | | 0.354730 | CATSv2 |
-| **Insgesamt** | **0.521** | **0.484** | **0.545** | **0.461** | **0.395** | **0.467** | **0.358** | | **0.465** | | **0.158** | | **0.399** | **Insgesamt** |
+| Datensatz | POLY | iForest | PCA | USAD | CNN | OmAn | LSTM | kShape | kMeans | OCSVM | LOF | Sub-LOF | KNN | Datensatz |
+| ------------- | --------- | --------- | --------- | --------- | --------- | --------- | --------- | ------ | --------- | ----- | --------- | --------- | --------- | ------------- |
+| SMD | 0.482296 | 0.322146 | 0.423162 | 0.519965 | 0.503535 | 0.410939 | 0.453416 | | 0.092843 | | 0.137760 | 0.457631 | 0.063644 | SMD |
+| YAHOO | 0.518566 | 0.936245 | 0.568333 | 0.354527 | 0.351064 | 0.354507 | 0.348855 | | 0.477510 | | 0.304093 | 0.188491 | 0.322916 | YAHOO |
+| Exathlon | 0.847945 | 0.964836 | 0.959173 | 0.864301 | 0.657757 | 0.876372 | 0.735253 | | 0.618051 | | 0.240338 | 0.262478 | 0.562449 | Exathlon |
+| NAB | 0.478372 | 0.285635 | 0.474780 | 0.262268 | 0.238264 | 0.326918 | 0.181686 | | 0.272775 | | 0.183564 | 0.511944 | 0.219327 | NAB |
+| OPPORTUNITY | 0.630618 | 0.868003 | 0.966351 | 0.660160 | 0.741769 | 0.660151 | 0.567052 | | 0.255118 | | 0.152842 | 0.139082 | 0.257788 | OPPORTUNITY |
+| WSD | 0.457794 | 0.038526 | 0.067564 | 0.086910 | 0.206990 | 0.087346 | 0.100554 | | 0.293116 | | 0.073377 | 0.608260 | 0.142998 | WSD |
+| SVDB | 0.423050 | 0.314567 | 0.508621 | 0.424770 | 0.206479 | 0.436465 | 0.131672 | | 0.804472 | | 0.052218 | 0.359030 | 0.579059 | SVDB |
+| SMAP | 0.891481 | 0.487664 | 0.951739 | 0.947702 | 0.237156 | 0.951635 | 0.223192 | | 0.946525 | | 0.046142 | 0.599966 | 0.818737 | SMAP |
+| IOPS | 0.426245 | 0.267117 | 0.422834 | 0.341683 | 0.312286 | 0.380533 | 0.334417 | | 0.112229 | | 0.302989 | 0.258387 | 0.111561 | IOPS |
+| TODS | 0.437694 | 0.174752 | 0.342464 | 0.336685 | 0.331028 | 0.338275 | 0.263210 | | 0.689051 | | 0.198760 | 0.600606 | 0.773793 | TODS |
+| MGAB | 0.008269 | 0.004379 | 0.005551 | 0.005403 | 0.006988 | 0.005586 | 0.025419 | | 0.036645 | | 0.004639 | 0.634748 | 0.238613 | MGAB |
+| MSL | 0.653967 | 0.514630 | 0.492975 | 0.142125 | 0.326973 | 0.412021 | 0.309296 | | 0.405174 | | 0.327778 | 0.487796 | 0.303536 | MSL |
+| NEK | 0.628709 | 0.678337 | 0.880822 | 0.868114 | 0.756555 | 0.884225 | 0.704672 | | 0.298379 | | 0.392335 | 0.597690 | 0.162564 | NEK |
+| LTDB | 0.510507 | 0.566359 | 0.534873 | 0.512266 | 0.406171 | 0.524763 | 0.329828 | | 0.835553 | | 0.256447 | 0.409530 | 0.692355 | LTDB |
+| MITDB | 0.320425 | 0.159042 | 0.323526 | 0.158357 | 0.143632 | 0.163465 | 0.112398 | | 0.590892 | | 0.053749 | 0.367125 | 0.548995 | MITDB |
+| SED | 0.040176 | 0.807209 | 0.030270 | 0.053374 | 0.058416 | 0.055985 | 0.056562 | | 0.895291 | | 0.111105 | 0.253420 | 0.882987 | SED |
+| Daphnet | 0.519516 | 0.518905 | 0.441568 | 0.122992 | 0.398456 | 0.123026 | 0.133080 | | 0.039747 | | 0.134804 | 0.253956 | 0.035185 | Daphnet |
+| SWaT | 0.103364 | 0.368230 | 0.375512 | 0.365922 | 0.680748 | 0.366250 | 0.669824 | | 0.111519 | | 0.121168 | 0.113915 | 0.110850 | SWaT |
+| Power | 0.122294 | 0.076373 | 0.079616 | 0.067090 | 0.075487 | 0.067090 | 0.067250 | | 0.524166 | | 0.090503 | 0.160858 | 0.166562 | Power |
+| CATSv2 | 0.232252 | 0.105175 | 0.232417 | 0.406831 | 0.288293 | 0.282282 | 0.329056 | | 0.229268 | | 0.063826 | 0.393045 | 0.354730 | CATSv2 |
+| **Insgesamt** | **0.521** | **0.484** | **0.545** | **0.461** | **0.395** | **0.467** | **0.358** | | **0.465** | | **0.158** | **0.393** | **0.399** | **Insgesamt** |
# POLY:
+ Prozessor: CPU
@@ -635,37 +635,41 @@
**Evaluation:**
+ Durchschnitt Gesamt:
- + Recall:
- + Precision:
- + Standard-F1: (vgl. 0.24)
- + Auc-Roc: (vgl. 0.68)
- + Auc-PR: (vgl. 0.16)
- + Vus-PR: (vgl. 0.25)
+ + Recall: 0.420
+ + Precision: 0.345
+ + Standard-F1: 0.450 (vgl. 0.24, + 0.210, $\approx$ 87.5 %)
+ + Auc-Roc: 0.794 (vgl. 0.68, + 0.114, $\approx$ 16.8 %)
+ + Auc-PR: 0.374 (vgl. 0.16, + 0.214, $\approx$ 133.8 %)
+ + Vus-PR: 0.473 (vgl. 0.25, + 0.223, $\approx$ 89.2 %)
+ Durchschnitt Punktanomalien:
- + Recall:
- + Precision:
- + Standard-F1:
- + Auc-Roc:
- + Auc-PR:
- + Vus-PR:
+ + Recall: 0.433
+ + Precision: 0.077
+ + Standard-F1: 0.207
+ + Auc-Roc: 0.831
+ + Auc-PR: 0.131
+ + Vus-PR: 0.514
+ Durchschnitt Sequenzanomalien:
- + Recall:
- + Precision:
- + Standard-F1:
- + Auc-Roc:
- + Auc-PR:
- + Vus-PR:
+ + Recall: 0.261
+ + Precision: 0.397
+ + Standard-F1: 0.418
+ + Auc-Roc: 0.726
+ + Auc-PR: 0.330
+ + Vus-PR: 0.393
**Bemerkung:**
-+ Deutlich besser bei -anomalien
++ Deutlich besser bei Sequenzanomalien nach AUC-PR, nach VUS-PR bei Punktanomalien
++ Bei MGAB, wo viele Modelle Probleme haben (VUS-PR und AUC-PR zw. 0.05 und 0.00) hat Sub-LOF eine AUC-PR von 0.57 und VUS-PR von 0.63
++ Beste Performanz auf MGAB auch bei Autoren
++ Große Differenzen zw. AUC-PR und VUS-pr bei Stock (0.115 vs. 0.748), TAO (0.140 vs. 0.808) und TODS (0.167 vs. 0.691)
++ Nur auf dem Yahoo Datensatz (nach AUC-PR, nach VUS-PR nicht!) ist LOF deutlich besser als Sub-LOF (also der Durchlauf in einem batch anstelle mittels sliding windows)
+ Beste erkannte Gruppe:
+ nach AUC-PR:
- +
+ + MGAB: 0.567335 (TAO: 0.139803)
+ nach VUS-PR:
- + (vgl. TAO 0.92)
+ + TAO: 0.807694 (vgl. TAO 0.92; MGAB: 0.634748, vgl. MGAB: 0.44)
+ Schlechteste erkannte Gruppe:
+ nach AUC-PR:
- +
+ + SED: 0.109660 (SWaT: 0.113563; WSD: 0.539254)
+ nach VUS-PR:
+ (vgl. WSD 0.03)
+ Im Gegensatz zur schlechten Performanz der anderen Modelle auf dem Datensatz **MGAB** hat Sub-LOF bei den Autoren hier ein Vus-PR von **0.44**
diff --git a/docs/evaluation/groupedDataframes/AUC-PR_combined_by_group.csv b/docs/evaluation/groupedDataframes/AUC-PR_combined_by_group.csv
index df1eb8d0c5abf10a493928258c5d439f7c205e87..7bcdde61476512afdaedb8412610ec43bcc4fabf 100644
--- a/docs/evaluation/groupedDataframes/AUC-PR_combined_by_group.csv
+++ b/docs/evaluation/groupedDataframes/AUC-PR_combined_by_group.csv
@@ -1,11 +1,12 @@
-,Model,SVDB,Power,MGAB,Daphnet,WSD,SMAP,MSL,Exathlon,Stock,IOPS,UCR,YAHOO,NAB,LTDB,MITDB,SMD,TODS,SWaT,NEK,OPPORTUNITY,SED,TAO,CATSv2
-0,CNN,0.19710262016040547,0.0723996101568745,0.003854961812131611,0.3814990500329981,0.30312825425966844,0.3299309288297937,0.30703296485567955,0.6543096941901486,0.9293442608636605,0.2658893118021881,0.06947703302366708,0.5615618691240216,0.22334685517173777,0.3544623948216704,0.1601528087440646,0.565369591802724,0.3037856723254471,0.7387181088941073,0.6855731430154801,0.6191602168303323,0.029325049402745367,0.9948566473921369,0.4118939698305733
-0,IForest,0.3119364827416871,0.0739812238848341,0.004336120023749678,0.4965785621747466,0.04099291102913815,0.2993019518138772,0.38608540888302983,0.9628064611603744,0.14393995693030376,0.23156929513103078,0.059389091972092405,0.09272991506414939,0.3145868144981536,0.5213405915521423,0.16955657029296148,0.36923736187055917,0.07652134064844376,0.7024320276028485,0.630339411513941,0.7331529032690003,0.691483898843896,0.12581675403237186,0.1394155160045949
-0,KMeansAD_U,0.8090356381810129,0.507629476682699,0.08529855686124818,0.0364448974253113,0.14637226924693936,0.6489127043129476,0.37143817671367996,0.617689617530909,0.11447566194398832,0.06871545205888992,0.48720584604063366,0.6994439310340633,0.401504819120054,0.7658193255633926,0.5838081485697818,0.2609082130751905,0.4487028103262184,0.1111516911833987,0.3469725689956081,0.3653810197119157,0.7105752596393731,0.12914709845456196,0.4556114877404176
-0,LOF,0.04493994647519603,0.0862447643103002,0.002208833983716011,0.129509098249193,0.14191760711722487,0.18079700554505512,0.15122846324983763,0.2451059410575724,0.11206072684081272,0.11678669465120142,0.0489848149626439,0.4099090939695364,0.1448442788333725,0.20324070530989097,0.05162771249827228,0.18235312998281822,0.10081987259876368,0.1206834698967151,0.36356090912215866,0.15339581045465292,0.08219767855332698,0.1679948274250915,0.0715421233322276
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-0,OmniAnomaly,0.4768352264302811,0.0646648482156372,0.015268247817355054,0.1920691814960085,0.251057174157317,0.38508194752955704,0.39428271688844074,0.8745189065767695,0.13364632394088924,0.36816289562529086,0.08523551844806315,0.1481883731109026,0.3322271540944519,0.4797110125580823,0.20699912890412075,0.5311401685436009,0.17236897672776852,0.7576872065528726,0.8361454306772048,0.6498671005600911,0.031663480582993765,0.344060221602637,0.4378677976960084
-0,PCA,0.5588963799777975,0.0788664308035282,0.027122742026965137,0.468647067072471,0.21654161409334477,0.4844163013142009,0.4933200185137532,0.9581020113822701,0.14842805522832,0.3728494779469234,0.1385328677464032,0.1171068241297201,0.48652829694101696,0.4894113142147856,0.3778533754675271,0.4958507799477434,0.12432056705472291,0.7567001273773122,0.891733187275396,0.9231919377778752,0.0209941892398622,0.1491442049585928,0.4747050350102691
-0,POLY,0.50600229760421,0.2037595305274893,0.008995606099947298,0.5368267899294596,0.42738732029834203,0.6048262003837879,0.629532587636957,0.844512912662751,0.14659009081554358,0.3328661662243327,0.15685006774098753,0.0753954175292419,0.5264388130929107,0.4553236691053208,0.3669341487796059,0.6393941543831635,0.2390237154249407,0.1231331999424481,0.7094581583655936,0.4206576520060393,0.03142142379603057,0.1405259120954581,0.4764337820823609
-0,Sub_KNN,0.5382699167825771,0.1601672827617932,0.32564999100566705,0.0338932937578225,0.044597067463582274,0.4538159096946783,0.313525013097462,0.563481394957596,0.0961032782898458,0.07059816232194295,0.2838297601145142,0.14444537624494838,0.31109955913147375,0.5898283428336337,0.500833656234517,0.16297042908781798,0.41064853826364733,0.1103758314980202,0.11917378259905748,0.2983959722264093,0.7074528685504887,0.10873282764385776,0.4821662398986781
-0,USAD,0.4592092425862558,0.0646645958264565,0.032096908715701186,0.1920565328650643,0.2402758256128196,0.27315882208579156,0.26725560751582494,0.8623584859187469,0.13357031995417967,0.40352305115361864,0.08839193854672213,0.11726577742217488,0.30030480702906,0.4613347441601701,0.20180998220768165,0.6657365297403594,0.1639152198541356,0.7574841555865873,0.8160210681956586,0.651234598743209,0.026230704465697034,0.3397807769750269,0.4816245755217306
+,Model,IOPS,SWaT,SED,MSL,SVDB,MGAB,LTDB,SMAP,Daphnet,Stock,WSD,MITDB,UCR,Power,NEK,CATSv2,NAB,Exathlon,TAO,OPPORTUNITY,TODS,SMD,YAHOO
+0,CNN,0.2658893118021881,0.7387181088941073,0.029325049402745367,0.30703296485567955,0.19710262016040547,0.003854961812131611,0.3544623948216704,0.3299309288297937,0.3814990500329981,0.9293442608636605,0.30312825425966844,0.1601528087440646,0.06947703302366708,0.0723996101568745,0.6855731430154801,0.4118939698305733,0.22334685517173777,0.6543096941901486,0.9948566473921369,0.6191602168303323,0.3037856723254471,0.565369591802724,0.5615618691240216
+0,IForest,0.23156929513103078,0.7024320276028485,0.691483898843896,0.38608540888302983,0.3119364827416871,0.004336120023749678,0.5213405915521423,0.2993019518138772,0.4965785621747466,0.14393995693030376,0.04099291102913815,0.16955657029296148,0.059389091972092405,0.0739812238848341,0.630339411513941,0.1394155160045949,0.3145868144981536,0.9628064611603744,0.12581675403237186,0.7331529032690003,0.07652134064844376,0.36923736187055917,0.09272991506414939
+0,KMeansAD_U,0.06871545205888992,0.1111516911833987,0.7105752596393731,0.37143817671367996,0.8090356381810129,0.08529855686124818,0.7658193255633926,0.6489127043129476,0.0364448974253113,0.11447566194398832,0.14637226924693936,0.5838081485697818,0.48720584604063366,0.507629476682699,0.3469725689956081,0.4556114877404176,0.401504819120054,0.617689617530909,0.12914709845456196,0.3653810197119157,0.4487028103262184,0.2609082130751905,0.6994439310340633
+0,LOF,0.11678669465120142,0.1206834698967151,0.08219767855332698,0.15122846324983763,0.04493994647519603,0.002208833983716011,0.20324070530989097,0.18079700554505512,0.129509098249193,0.11206072684081272,0.14191760711722487,0.05162771249827228,0.0489848149626439,0.0862447643103002,0.36356090912215866,0.0715421233322276,0.1448442788333725,0.2451059410575724,0.1679948274250915,0.15339581045465292,0.10081987259876368,0.18235312998281822,0.4099090939695364
+0,LSTMAD,0.3201945495278017,0.7376946947277406,0.030497343412870064,0.23744155439224032,0.12987864790676196,0.04585981775047413,0.27673530608030433,0.2788270775280182,0.1322337577607795,0.5192324559661586,0.20949249626949865,0.11306591669413261,0.028041338054278185,0.0647879297198734,0.6674208880035603,0.3580709697520762,0.1533056834456119,0.733874544363356,0.9933974763498682,0.5455348153510139,0.20567074108559213,0.5398904963082672,0.4439573166657559
+0,OmniAnomaly,0.36816289562529086,0.7576872065528726,0.031663480582993765,0.39428271688844074,0.4768352264302811,0.015268247817355054,0.4797110125580823,0.38508194752955704,0.1920691814960085,0.13364632394088924,0.251057174157317,0.20699912890412075,0.08523551844806315,0.0646648482156372,0.8361454306772048,0.4378677976960084,0.3322271540944519,0.8745189065767695,0.344060221602637,0.6498671005600911,0.17236897672776852,0.5311401685436009,0.1481883731109026
+0,PCA,0.3728494779469234,0.7567001273773122,0.0209941892398622,0.4933200185137532,0.5588963799777975,0.027122742026965137,0.4894113142147856,0.4844163013142009,0.468647067072471,0.14842805522832,0.21654161409334477,0.3778533754675271,0.1385328677464032,0.0788664308035282,0.891733187275396,0.4747050350102691,0.48652829694101696,0.9581020113822701,0.1491442049585928,0.9231919377778752,0.12432056705472291,0.4958507799477434,0.1171068241297201
+0,POLY,0.3328661662243327,0.1231331999424481,0.03142142379603057,0.629532587636957,0.50600229760421,0.008995606099947298,0.4553236691053208,0.6048262003837879,0.5368267899294596,0.14659009081554358,0.42738732029834203,0.3669341487796059,0.15685006774098753,0.2037595305274893,0.7094581583655936,0.4764337820823609,0.5264388130929107,0.844512912662751,0.1405259120954581,0.4206576520060393,0.2390237154249407,0.6393941543831635,0.0753954175292419
+0,Sub-LOF,0.26349163914256646,0.1135633808365225,0.10965998852146776,0.4426697426987531,0.35614017676232956,0.5673347974410752,0.33316020067643426,0.5103409692815175,0.2522823807762812,0.1150331890223664,0.5392539833042346,0.38519489390955175,0.4951819333128137,0.1750346138359664,0.5545055713305032,0.5119762791999092,0.495380602802276,0.2576177402577311,0.13980310215956185,0.1586532880262183,0.16650708100479605,0.4863069423901577,0.15050272371074025
+0,Sub_KNN,0.07059816232194295,0.1103758314980202,0.7074528685504887,0.313525013097462,0.5382699167825771,0.32564999100566705,0.5898283428336337,0.4538159096946783,0.0338932937578225,0.0961032782898458,0.044597067463582274,0.500833656234517,0.2838297601145142,0.1601672827617932,0.11917378259905748,0.4821662398986781,0.31109955913147375,0.563481394957596,0.10873282764385776,0.2983959722264093,0.41064853826364733,0.16297042908781798,0.14444537624494838
+0,USAD,0.40352305115361864,0.7574841555865873,0.026230704465697034,0.26725560751582494,0.4592092425862558,0.032096908715701186,0.4613347441601701,0.27315882208579156,0.1920565328650643,0.13357031995417967,0.2402758256128196,0.20180998220768165,0.08839193854672213,0.0646645958264565,0.8160210681956586,0.4816245755217306,0.30030480702906,0.8623584859187469,0.3397807769750269,0.651234598743209,0.1639152198541356,0.6657365297403594,0.11726577742217488
diff --git a/docs/evaluation/groupedDataframes/VUS-PR_combined_by_group.csv b/docs/evaluation/groupedDataframes/VUS-PR_combined_by_group.csv
index ad323dcef01fe398c7b73b516b9a71fabd13dc71..4bc325d198cbaa4ccf184c9ff7b250bc98a207d1 100644
--- a/docs/evaluation/groupedDataframes/VUS-PR_combined_by_group.csv
+++ b/docs/evaluation/groupedDataframes/VUS-PR_combined_by_group.csv
@@ -1,11 +1,12 @@
-,Model,SVDB,Power,MGAB,Daphnet,WSD,SMAP,MSL,Exathlon,Stock,IOPS,UCR,YAHOO,NAB,LTDB,MITDB,SMD,TODS,SWaT,NEK,OPPORTUNITY,SED,TAO,CATSv2
-0,CNN,0.1997846992126922,0.0754866098747693,0.0069880026447859105,0.3984561332333746,0.22492161972936892,0.3368175788334636,0.34635004588200624,0.6577570780079647,0.9399247021670545,0.20582640755044848,0.06544275611727057,0.5120964005826543,0.24809064327969454,0.40617143072486417,0.14363186026434818,0.5450449067296064,0.575941184620618,0.6807482076261672,0.7148450524753189,0.6327991152012451,0.058416114173648566,0.9942696053962238,0.2882929464081713
-0,IForest,0.3073223626012233,0.0763734881882089,0.004379386516480511,0.5189053892717354,0.027486988072735103,0.32772652007428976,0.4487088378075529,0.9648356800808771,0.7358859795437948,0.1345180317161169,0.058772878606051945,0.13566389910342985,0.3421369664041377,0.5663593089308047,0.15904247331707733,0.3424058241109849,0.48738632960300915,0.3682300481513787,0.6497347597115171,0.7362636520011094,0.8072091746326211,0.7289704865874446,0.105174922263832
-0,KMeansAD_U,0.8113847695158117,0.5241664765771313,0.03664497423359471,0.0397474048677725,0.17306040829201394,0.6577379563617795,0.4415431287006482,0.6180514515785507,0.7381976474065515,0.1079882871672322,0.48682179418842214,0.78182374346563,0.42747718824263387,0.8355528232967653,0.5908924511486201,0.2545373617228621,0.7392574120062714,0.1115190303707684,0.3179274541052912,0.3518276749123187,0.8952913367248847,0.7479454637274009,0.2292684024148795
-0,LOF,0.05018881896775702,0.0905025385600026,0.004638573553949167,0.1348036345450808,0.1023455399207899,0.17249913092558428,0.1867000262952127,0.24033784675388556,0.7104868086713348,0.12365662810007907,0.05148903079187264,0.3815083295900898,0.16596623628732607,0.25644727824547736,0.05374869341290776,0.13498525799790392,0.4850789687207982,0.1211682396739051,0.39512958234640544,0.1591996538121128,0.11110536628014576,0.7105835188005747,0.0638260310723236
-0,LSTMAD,0.12748852543364644,0.0672501040011019,0.02541916388299069,0.1330800298859931,0.13026969854826323,0.273213536450389,0.30512791043157395,0.735253231133451,0.8179595058481393,0.2130441268776781,0.023292741312739982,0.4174161081456283,0.17373197532380166,0.32982840878783637,0.11239751245844268,0.48394405976309657,0.5222277602405662,0.669824054008361,0.6896972412727194,0.5637720546144361,0.056562170107036035,0.9950444582863889,0.3290558627970383
-0,OmniAnomaly,0.445289118136039,0.0670900075295742,0.005586448237557389,0.1230261153960334,0.15761230831578144,0.4178519668986689,0.4280475527739124,0.8763722516375352,0.7716583853918693,0.1928374569986444,0.08955150737058691,0.21978699689042347,0.34200742217457203,0.5247628039733387,0.16346484655995386,0.47874214848138164,0.5381935047574228,0.366250384309729,0.8583489172841368,0.6499305118412632,0.055985189981857066,0.9300201627687462,0.2822817568231803
-0,PCA,0.5239841979223827,0.0796163424706734,0.005551113652017667,0.4415678196838903,0.15536603262796655,0.5668421229644969,0.5233099809194475,0.9591725273812642,0.8253823808338303,0.2603723461255518,0.1526782948310656,0.1637287767285993,0.5113983091235315,0.5348733977584581,0.32352578503655105,0.4672566855173588,0.5528774654894228,0.3755116281521825,0.9291709818321476,0.9245164887480816,0.030269609217551566,0.8402761677661017,0.2324174649783961
-0,POLY,0.4455308354706224,0.1222940559336612,0.008268735555270955,0.5195156603941771,0.5311097529528253,0.7270794225766999,0.7342443893083611,0.8479450729850164,0.8053753836898458,0.36505488384910495,0.19877971115578724,0.3076533188880135,0.58411151200798,0.5105066913376546,0.3204245599085764,0.6631912450676738,0.5864932357832445,0.1033636962969695,0.7648360444393737,0.4263263694845811,0.040175651318865566,0.8084529309725733,0.232251680558134
-0,Sub_KNN,0.5914836251513862,0.1665616569474886,0.23861305462798313,0.0351848897952167,0.08320386434254905,0.5582867850000348,0.3687456862707051,0.5624491502491966,0.6915117129467715,0.11652716789354169,0.32974766955827883,0.5020311037216072,0.3414322714780459,0.6923549140356251,0.5489948037487509,0.16380278316830532,0.7802797461321267,0.1108500020039233,0.13290842186836746,0.29539772741997733,0.882987455118878,0.6841191787952137,0.3547303318013108
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+,Model,IOPS,SWaT,SED,MSL,SVDB,MGAB,LTDB,SMAP,Daphnet,Stock,WSD,MITDB,UCR,Power,NEK,CATSv2,NAB,Exathlon,TAO,OPPORTUNITY,TODS,SMD,YAHOO
+0,CNN,0.20582640755044848,0.6807482076261672,0.058416114173648566,0.34635004588200624,0.1997846992126922,0.0069880026447859105,0.40617143072486417,0.3368175788334636,0.3984561332333746,0.9399247021670545,0.22492161972936892,0.14363186026434818,0.06544275611727057,0.0754866098747693,0.7148450524753189,0.2882929464081713,0.24809064327969454,0.6577570780079647,0.9942696053962238,0.6327991152012451,0.575941184620618,0.5450449067296064,0.5120964005826543
+0,IForest,0.1345180317161169,0.3682300481513787,0.8072091746326211,0.4487088378075529,0.3073223626012233,0.004379386516480511,0.5663593089308047,0.32772652007428976,0.5189053892717354,0.7358859795437948,0.027486988072735103,0.15904247331707733,0.058772878606051945,0.0763734881882089,0.6497347597115171,0.105174922263832,0.3421369664041377,0.9648356800808771,0.7289704865874446,0.7362636520011094,0.48738632960300915,0.3424058241109849,0.13566389910342985
+0,KMeansAD_U,0.1079882871672322,0.1115190303707684,0.8952913367248847,0.4415431287006482,0.8113847695158117,0.03664497423359471,0.8355528232967653,0.6577379563617795,0.0397474048677725,0.7381976474065515,0.17306040829201394,0.5908924511486201,0.48682179418842214,0.5241664765771313,0.3179274541052912,0.2292684024148795,0.42747718824263387,0.6180514515785507,0.7479454637274009,0.3518276749123187,0.7392574120062714,0.2545373617228621,0.78182374346563
+0,LOF,0.12365662810007907,0.1211682396739051,0.11110536628014576,0.1867000262952127,0.05018881896775702,0.004638573553949167,0.25644727824547736,0.17249913092558428,0.1348036345450808,0.7104868086713348,0.1023455399207899,0.05374869341290776,0.05148903079187264,0.0905025385600026,0.39512958234640544,0.0638260310723236,0.16596623628732607,0.24033784675388556,0.7105835188005747,0.1591996538121128,0.4850789687207982,0.13498525799790392,0.3815083295900898
+0,LSTMAD,0.2130441268776781,0.669824054008361,0.056562170107036035,0.30512791043157395,0.12748852543364644,0.02541916388299069,0.32982840878783637,0.273213536450389,0.1330800298859931,0.8179595058481393,0.13026969854826323,0.11239751245844268,0.023292741312739982,0.0672501040011019,0.6896972412727194,0.3290558627970383,0.17373197532380166,0.735253231133451,0.9950444582863889,0.5637720546144361,0.5222277602405662,0.48394405976309657,0.4174161081456283
+0,OmniAnomaly,0.1928374569986444,0.366250384309729,0.055985189981857066,0.4280475527739124,0.445289118136039,0.005586448237557389,0.5247628039733387,0.4178519668986689,0.1230261153960334,0.7716583853918693,0.15761230831578144,0.16346484655995386,0.08955150737058691,0.0670900075295742,0.8583489172841368,0.2822817568231803,0.34200742217457203,0.8763722516375352,0.9300201627687462,0.6499305118412632,0.5381935047574228,0.47874214848138164,0.21978699689042347
+0,PCA,0.2603723461255518,0.3755116281521825,0.030269609217551566,0.5233099809194475,0.5239841979223827,0.005551113652017667,0.5348733977584581,0.5668421229644969,0.4415678196838903,0.8253823808338303,0.15536603262796655,0.32352578503655105,0.1526782948310656,0.0796163424706734,0.9291709818321476,0.2324174649783961,0.5113983091235315,0.9591725273812642,0.8402761677661017,0.9245164887480816,0.5528774654894228,0.4672566855173588,0.1637287767285993
+0,POLY,0.36505488384910495,0.1033636962969695,0.040175651318865566,0.7342443893083611,0.4455308354706224,0.008268735555270955,0.5105066913376546,0.7270794225766999,0.5195156603941771,0.8053753836898458,0.5311097529528253,0.3204245599085764,0.19877971115578724,0.1222940559336612,0.7648360444393737,0.232251680558134,0.58411151200798,0.8479450729850164,0.8084529309725733,0.4263263694845811,0.5864932357832445,0.6631912450676738,0.3076533188880135
+0,Sub-LOF,0.380816999613631,0.1139147000964346,0.25341982469633156,0.5447112510432905,0.38299993831393025,0.6347484664935239,0.4095296341228547,0.5978537468587533,0.2539555253290684,0.7475672197205663,0.5510409756112902,0.3671251716842331,0.5143263768552852,0.1608581709679401,0.6870198283873492,0.3930451961624531,0.5324501908617666,0.2624784786359157,0.8076936745400151,0.1495480597705363,0.691124998860781,0.5446962631623808,0.4510005840593197
+0,Sub_KNN,0.11652716789354169,0.1108500020039233,0.882987455118878,0.3687456862707051,0.5914836251513862,0.23861305462798313,0.6923549140356251,0.5582867850000348,0.0351848897952167,0.6915117129467715,0.08320386434254905,0.5489948037487509,0.32974766955827883,0.1665616569474886,0.13290842186836746,0.3547303318013108,0.3414322714780459,0.5624491502491966,0.6841191787952137,0.29539772741997733,0.7802797461321267,0.16380278316830532,0.5020311037216072
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diff --git a/src/group_evaluation/create_combined_dataframe_with_metrics_and_plot.ipynb b/src/group_evaluation/create_combined_dataframe_with_metrics_and_plot.ipynb
index adada2ee0357bd3a6168f7029babf2e0c9052a17..e044f4338385605f475d812cc0c7513a7b7a9373 100644
--- a/src/group_evaluation/create_combined_dataframe_with_metrics_and_plot.ipynb
+++ b/src/group_evaluation/create_combined_dataframe_with_metrics_and_plot.ipynb
@@ -2,7 +2,7 @@
"cells": [
{
"cell_type": "code",
- "execution_count": 1,
+ "execution_count": 26,
"metadata": {},
"outputs": [],
"source": [
@@ -13,7 +13,7 @@
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": 27,
"metadata": {},
"outputs": [
{
@@ -29,6 +29,7 @@
"Found: OmniAnomaly.csv\n",
"Found: PCA.csv\n",
"Found: POLY.csv\n",
+ "Found: Sub-LOF.csv\n",
"Found: Sub_KNN.csv\n",
"Not correct file type: temp\n",
"Found: USAD.csv\n",
@@ -62,7 +63,7 @@
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": 28,
"metadata": {},
"outputs": [
{
@@ -253,7 +254,7 @@
"4 0.232558 CNN "
]
},
- "execution_count": 4,
+ "execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
@@ -264,16 +265,16 @@
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": 29,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "(3970, 18)"
+ "(4367, 18)"
]
},
- "execution_count": 5,
+ "execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
@@ -284,7 +285,7 @@
},
{
"cell_type": "code",
- "execution_count": 32,
+ "execution_count": 30,
"metadata": {},
"outputs": [
{
@@ -299,12 +300,13 @@
"OmniAnomaly 397\n",
"PCA 397\n",
"POLY 397\n",
+ "Sub-LOF 397\n",
"Sub_KNN 397\n",
"USAD 397\n",
"Name: count, dtype: int64"
]
},
- "execution_count": 32,
+ "execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
@@ -315,7 +317,7 @@
},
{
"cell_type": "code",
- "execution_count": 39,
+ "execution_count": 31,
"metadata": {},
"outputs": [],
"source": [
@@ -330,7 +332,7 @@
" 'POLY': 'lightskyblue',\n",
" 'Sub_KNN': 'firebrick',#'gold' ,\n",
" 'USAD': 'mediumpurple',\n",
- " 'Sub_LOF':'firebrick' ,\n",
+ " 'Sub-LOF':'dodgerblue' ,\n",
" 'KShapeAD': 'darksalmon' ,\n",
" 'OCSVM': 'darkorange'\n",
"}"
@@ -338,7 +340,7 @@
},
{
"cell_type": "code",
- "execution_count": 40,
+ "execution_count": 32,
"metadata": {},
"outputs": [
{
@@ -360,7 +362,7 @@
"data": [
{
"alignmentgroup": "True",
- "hovertemplate": "Model=%{x}<br>AUC-PR=%{y}<extra></extra>",
+ "hovertemplate": "Model=%{x}<br>VUS-PR=%{y}<extra></extra>",
"legendgroup": "KMeansAD_U",
"marker": {
"color": "darkseagreen"
@@ -773,1233 +775,417 @@
"x0": " ",
"xaxis": "x",
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+ "#sort by average values\n",
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+ "\n",
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+ " 'y':0.94, \n",
+ " 'xanchor':'center',\n",
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+ " height=700,width=1000,\n",
+ " )\n",
+ "fig.update_traces(marker=dict(size=12,\n",
+ " opacity=0.8,\n",
+ " line=dict(width=2,\n",
+ " color='DarkSlateGrey'),\n",
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+ "cell_type": "code",
+ "execution_count": 41,
+ "metadata": {},
+ "outputs": [
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+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "c:\\Users\\desiw\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\plotly\\express\\_core.py:1985: FutureWarning:\n",
+ "\n",
+ "When grouping with a length-1 list-like, you will need to pass a length-1 tuple to get_group in a future version of pandas. Pass `(name,)` instead of `name` to silence this warning.\n",
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+ 18.46554386886001
+ ],
+ "yaxis": "y"
+ },
+ {
+ "alignmentgroup": "True",
+ "hovertemplate": "Model=%{x}<br>duration=%{y}<extra></extra>",
+ "legendgroup": "CNN",
+ "marker": {
+ "color": "steelblue",
+ "pattern": {
+ "shape": ""
+ }
+ },
+ "name": "CNN",
+ "offsetgroup": "CNN",
+ "orientation": "v",
+ "showlegend": true,
+ "textposition": "auto",
+ "type": "bar",
+ "x": [
+ "CNN"
+ ],
+ "xaxis": "x",
+ "y": [
+ 26.574519822819706
+ ],
+ "yaxis": "y"
+ },
+ {
+ "alignmentgroup": "True",
+ "hovertemplate": "Model=%{x}<br>duration=%{y}<extra></extra>",
+ "legendgroup": "USAD",
+ "marker": {
+ "color": "mediumpurple",
+ "pattern": {
+ "shape": ""
+ }
+ },
+ "name": "USAD",
+ "offsetgroup": "USAD",
+ "orientation": "v",
+ "showlegend": true,
+ "textposition": "auto",
+ "type": "bar",
+ "x": [
+ "USAD"
+ ],
+ "xaxis": "x",
+ "y": [
+ 28.923880110459603
+ ],
+ "yaxis": "y"
+ },
+ {
+ "alignmentgroup": "True",
+ "hovertemplate": "Model=%{x}<br>duration=%{y}<extra></extra>",
+ "legendgroup": "POLY",
+ "marker": {
+ "color": "lightskyblue",
+ "pattern": {
+ "shape": ""
+ }
+ },
+ "name": "POLY",
+ "offsetgroup": "POLY",
+ "orientation": "v",
+ "showlegend": true,
+ "textposition": "auto",
+ "type": "bar",
+ "x": [
+ "POLY"
+ ],
+ "xaxis": "x",
+ "y": [
+ 30.973502482815412
+ ],
+ "yaxis": "y"
+ },
+ {
+ "alignmentgroup": "True",
+ "hovertemplate": "Model=%{x}<br>duration=%{y}<extra></extra>",
+ "legendgroup": "OmniAnomaly",
+ "marker": {
+ "color": "slateblue",
+ "pattern": {
+ "shape": ""
+ }
+ },
+ "name": "OmniAnomaly",
+ "offsetgroup": "OmniAnomaly",
+ "orientation": "v",
+ "showlegend": true,
+ "textposition": "auto",
+ "type": "bar",
+ "x": [
+ "OmniAnomaly"
+ ],
+ "xaxis": "x",
+ "y": [
+ 31.020189434815414
+ ],
+ "yaxis": "y"
+ },
+ {
+ "alignmentgroup": "True",
+ "hovertemplate": "Model=%{x}<br>duration=%{y}<extra></extra>",
+ "legendgroup": "IForest",
+ "marker": {
+ "color": "darkmagenta",
+ "pattern": {
+ "shape": ""
+ }
+ },
+ "name": "IForest",
+ "offsetgroup": "IForest",
+ "orientation": "v",
+ "showlegend": true,
+ "textposition": "auto",
+ "type": "bar",
+ "x": [
+ "IForest"
+ ],
+ "xaxis": "x",
+ "y": [
+ 31.21474815135639
+ ],
+ "yaxis": "y"
+ },
+ {
+ "alignmentgroup": "True",
+ "hovertemplate": "Model=%{x}<br>duration=%{y}<extra></extra>",
+ "legendgroup": "LSTMAD",
+ "marker": {
+ "color": "blueviolet",
+ "pattern": {
+ "shape": ""
+ }
+ },
+ "name": "LSTMAD",
+ "offsetgroup": "LSTMAD",
+ "orientation": "v",
+ "showlegend": true,
+ "textposition": "auto",
+ "type": "bar",
+ "x": [
+ "LSTMAD"
+ ],
+ "xaxis": "x",
+ "y": [
+ 33.17645774320031
+ ],
+ "yaxis": "y"
+ },
+ {
+ "alignmentgroup": "True",
+ "hovertemplate": "Model=%{x}<br>duration=%{y}<extra></extra>",
+ "legendgroup": "PCA",
+ "marker": {
+ "color": "yellowgreen",
+ "pattern": {
+ "shape": ""
+ }
+ },
+ "name": "PCA",
+ "offsetgroup": "PCA",
+ "orientation": "v",
+ "showlegend": true,
+ "textposition": "auto",
+ "type": "bar",
+ "x": [
+ "PCA"
+ ],
+ "xaxis": "x",
+ "y": [
+ 38.65838090358513
+ ],
+ "yaxis": "y"
+ },
+ {
+ "alignmentgroup": "True",
+ "hovertemplate": "Model=%{x}<br>duration=%{y}<extra></extra>",
+ "legendgroup": "Sub-LOF",
+ "marker": {
+ "color": "dodgerblue",
+ "pattern": {
+ "shape": ""
+ }
+ },
+ "name": "Sub-LOF",
+ "offsetgroup": "Sub-LOF",
+ "orientation": "v",
+ "showlegend": true,
+ "textposition": "auto",
+ "type": "bar",
+ "x": [
+ "Sub-LOF"
+ ],
+ "xaxis": "x",
+ "y": [
+ 46.61300139823548
+ ],
+ "yaxis": "y"
+ },
+ {
+ "alignmentgroup": "True",
+ "hovertemplate": "Model=%{x}<br>duration=%{y}<extra></extra>",
+ "legendgroup": "KMeansAD_U",
+ "marker": {
+ "color": "darkseagreen",
+ "pattern": {
+ "shape": ""
+ }
+ },
+ "name": "KMeansAD_U",
+ "offsetgroup": "KMeansAD_U",
+ "orientation": "v",
+ "showlegend": true,
+ "textposition": "auto",
+ "type": "bar",
+ "x": [
+ "KMeansAD_U"
+ ],
+ "xaxis": "x",
+ "y": [
+ 50.93969483459627
+ ],
+ "yaxis": "y"
+ },
+ {
+ "alignmentgroup": "True",
+ "hovertemplate": "Model=%{x}<br>duration=%{y}<extra></extra>",
+ "legendgroup": "Sub_KNN",
+ "marker": {
+ "color": "firebrick",
+ "pattern": {
+ "shape": ""
+ }
+ },
+ "name": "Sub_KNN",
+ "offsetgroup": "Sub_KNN",
+ "orientation": "v",
+ "showlegend": true,
+ "textposition": "auto",
+ "type": "bar",
+ "x": [
+ "Sub_KNN"
+ ],
+ "xaxis": "x",
+ "y": [
+ 60.541785299027296
],
- "y0": " ",
"yaxis": "y"
}
],
"layout": {
- "boxmode": "overlay",
+ "barmode": "relative",
"height": 700,
"legend": {
"bgcolor": "white",
@@ -8539,7 +10334,7 @@
"text": "Group"
},
"tracegroupgap": 0,
- "x": 0.1,
+ "x": 0.02,
"y": -0.1
},
"margin": {
@@ -9108,7 +10903,7 @@
}
},
"title": {
- "text": "Vergleich der Performanz der Modelle anhand AUC-PR",
+ "text": "Vergleich der Laufzeiten der Modelle beim Training der einzelnen Zeitserien",
"x": 0.5,
"xanchor": "center",
"y": 0.94,
@@ -9118,16 +10913,17 @@
"xaxis": {
"anchor": "y",
"categoryarray": [
- "KMeansAD_U",
- "PCA",
- "POLY",
+ "LOF",
"CNN",
- "OmniAnomaly",
"USAD",
- "LSTMAD",
+ "POLY",
+ "OmniAnomaly",
"IForest",
- "Sub_KNN",
- "LOF"
+ "LSTMAD",
+ "PCA",
+ "Sub-LOF",
+ "KMeansAD_U",
+ "Sub_KNN"
],
"categoryorder": "array",
"domain": [
@@ -9147,7 +10943,7 @@
1
],
"title": {
- "text": "AUC-PR"
+ "text": "Durchschnittliche Laufzeit"
}
}
}
@@ -9158,13 +10954,14 @@
}
],
"source": [
- "metric = 'AUC-PR'\n",
+ "duration = 'duration'\n",
"#sort by average values\n",
- "mean_sorted = df.groupby(\"Model\")[metric].mean().sort_values(ascending=False).index\n",
+ "df_mean = df.groupby(\"Model\",as_index=False)[\"duration\"].mean()\n",
+ "mean_sorted = df_mean.sort_values(ascending=True, by='duration')['Model']\n",
"\n",
- "fig = px.box(df, x='Model', y=metric, color='Model', category_orders={'Model':mean_sorted}, color_discrete_map=colors)\n",
+ "fig = px.bar(df_mean, x='Model', y=duration, color='Model', category_orders={'Model':mean_sorted}, color_discrete_map=colors)\n",
"fig.update_layout( legend=dict(\n",
- " x=0.1,\n",
+ " x=0.02,\n",
" y=-0.1,\n",
" orientation=\"h\",\n",
" title_font_family=\"Times New Roman\",\n",
@@ -9180,7 +10977,7 @@
" ),\n",
" template = 'ggplot2',\n",
" title={\n",
- " 'text': 'Vergleich der Performanz der Modelle anhand '+ metric,\n",
+ " 'text': 'Vergleich der Laufzeiten der Modelle beim Training der einzelnen Zeitserien',\n",
" 'x':0.5,\n",
" 'y':0.94, \n",
" 'xanchor':'center',\n",
@@ -9193,7 +10990,9 @@
" color='DarkSlateGrey'),\n",
" ),\n",
" selector=dict(mode='markers'))\n",
- "fig.update_xaxes( dtick = 1,tickangle = 360)"
+ "fig.update_xaxes( dtick = 1,tickangle = 360)\n",
+ "fig.update_yaxes( title='Durchschnittliche Laufzeit')\n",
+ "fig.show()"
]
},
{
diff --git a/src/group_evaluation/create_heatmap.ipynb b/src/group_evaluation/create_heatmap.ipynb
index 712e2c92cc64fe2e56981be655369199c630f477..6b470f6e258502f987cbc38d5bacf62e5de5bd9e 100644
--- a/src/group_evaluation/create_heatmap.ipynb
+++ b/src/group_evaluation/create_heatmap.ipynb
@@ -12,7 +12,7 @@
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": 10,
"metadata": {},
"outputs": [
{
@@ -36,27 +36,27 @@
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
+ " <th>IOPS</th>\n",
+ " <th>SWaT</th>\n",
+ " <th>SED</th>\n",
+ " <th>MSL</th>\n",
" <th>SVDB</th>\n",
- " <th>Power</th>\n",
" <th>MGAB</th>\n",
- " <th>Daphnet</th>\n",
- " <th>WSD</th>\n",
+ " <th>LTDB</th>\n",
" <th>SMAP</th>\n",
- " <th>MSL</th>\n",
- " <th>Exathlon</th>\n",
+ " <th>Daphnet</th>\n",
" <th>Stock</th>\n",
- " <th>IOPS</th>\n",
" <th>...</th>\n",
- " <th>LTDB</th>\n",
- " <th>MITDB</th>\n",
- " <th>SMD</th>\n",
- " <th>TODS</th>\n",
- " <th>SWaT</th>\n",
+ " <th>Power</th>\n",
" <th>NEK</th>\n",
- " <th>OPPORTUNITY</th>\n",
- " <th>SED</th>\n",
- " <th>TAO</th>\n",
" <th>CATSv2</th>\n",
+ " <th>NAB</th>\n",
+ " <th>Exathlon</th>\n",
+ " <th>TAO</th>\n",
+ " <th>OPPORTUNITY</th>\n",
+ " <th>TODS</th>\n",
+ " <th>SMD</th>\n",
+ " <th>YAHOO</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Model</th>\n",
@@ -86,123 +86,123 @@
" <tbody>\n",
" <tr>\n",
" <th>CNN</th>\n",
+ " <td>0.205826</td>\n",
+ " <td>0.680748</td>\n",
+ " <td>0.058416</td>\n",
+ " <td>0.346350</td>\n",
" <td>0.199785</td>\n",
- " <td>0.075487</td>\n",
" <td>0.006988</td>\n",
- " <td>0.398456</td>\n",
- " <td>0.224922</td>\n",
+ " <td>0.406171</td>\n",
" <td>0.336818</td>\n",
- " <td>0.346350</td>\n",
- " <td>0.657757</td>\n",
+ " <td>0.398456</td>\n",
" <td>0.939925</td>\n",
- " <td>0.205826</td>\n",
" <td>...</td>\n",
- " <td>0.406171</td>\n",
- " <td>0.143632</td>\n",
- " <td>0.545045</td>\n",
- " <td>0.575941</td>\n",
- " <td>0.680748</td>\n",
+ " <td>0.075487</td>\n",
" <td>0.714845</td>\n",
- " <td>0.632799</td>\n",
- " <td>0.058416</td>\n",
- " <td>0.994270</td>\n",
" <td>0.288293</td>\n",
+ " <td>0.248091</td>\n",
+ " <td>0.657757</td>\n",
+ " <td>0.994270</td>\n",
+ " <td>0.632799</td>\n",
+ " <td>0.575941</td>\n",
+ " <td>0.545045</td>\n",
+ " <td>0.512096</td>\n",
" </tr>\n",
" <tr>\n",
" <th>IForest</th>\n",
+ " <td>0.134518</td>\n",
+ " <td>0.368230</td>\n",
+ " <td>0.807209</td>\n",
+ " <td>0.448709</td>\n",
" <td>0.307322</td>\n",
- " <td>0.076373</td>\n",
" <td>0.004379</td>\n",
- " <td>0.518905</td>\n",
- " <td>0.027487</td>\n",
+ " <td>0.566359</td>\n",
" <td>0.327727</td>\n",
- " <td>0.448709</td>\n",
- " <td>0.964836</td>\n",
+ " <td>0.518905</td>\n",
" <td>0.735886</td>\n",
- " <td>0.134518</td>\n",
" <td>...</td>\n",
- " <td>0.566359</td>\n",
- " <td>0.159042</td>\n",
- " <td>0.342406</td>\n",
- " <td>0.487386</td>\n",
- " <td>0.368230</td>\n",
+ " <td>0.076373</td>\n",
" <td>0.649735</td>\n",
- " <td>0.736264</td>\n",
- " <td>0.807209</td>\n",
- " <td>0.728970</td>\n",
" <td>0.105175</td>\n",
+ " <td>0.342137</td>\n",
+ " <td>0.964836</td>\n",
+ " <td>0.728970</td>\n",
+ " <td>0.736264</td>\n",
+ " <td>0.487386</td>\n",
+ " <td>0.342406</td>\n",
+ " <td>0.135664</td>\n",
" </tr>\n",
" <tr>\n",
" <th>KMeansAD_U</th>\n",
+ " <td>0.107988</td>\n",
+ " <td>0.111519</td>\n",
+ " <td>0.895291</td>\n",
+ " <td>0.441543</td>\n",
" <td>0.811385</td>\n",
- " <td>0.524166</td>\n",
" <td>0.036645</td>\n",
- " <td>0.039747</td>\n",
- " <td>0.173060</td>\n",
+ " <td>0.835553</td>\n",
" <td>0.657738</td>\n",
- " <td>0.441543</td>\n",
- " <td>0.618051</td>\n",
+ " <td>0.039747</td>\n",
" <td>0.738198</td>\n",
- " <td>0.107988</td>\n",
" <td>...</td>\n",
- " <td>0.835553</td>\n",
- " <td>0.590892</td>\n",
- " <td>0.254537</td>\n",
- " <td>0.739257</td>\n",
- " <td>0.111519</td>\n",
+ " <td>0.524166</td>\n",
" <td>0.317927</td>\n",
- " <td>0.351828</td>\n",
- " <td>0.895291</td>\n",
- " <td>0.747945</td>\n",
" <td>0.229268</td>\n",
+ " <td>0.427477</td>\n",
+ " <td>0.618051</td>\n",
+ " <td>0.747945</td>\n",
+ " <td>0.351828</td>\n",
+ " <td>0.739257</td>\n",
+ " <td>0.254537</td>\n",
+ " <td>0.781824</td>\n",
" </tr>\n",
" <tr>\n",
" <th>LOF</th>\n",
+ " <td>0.123657</td>\n",
+ " <td>0.121168</td>\n",
+ " <td>0.111105</td>\n",
+ " <td>0.186700</td>\n",
" <td>0.050189</td>\n",
- " <td>0.090503</td>\n",
" <td>0.004639</td>\n",
- " <td>0.134804</td>\n",
- " <td>0.102346</td>\n",
+ " <td>0.256447</td>\n",
" <td>0.172499</td>\n",
- " <td>0.186700</td>\n",
- " <td>0.240338</td>\n",
+ " <td>0.134804</td>\n",
" <td>0.710487</td>\n",
- " <td>0.123657</td>\n",
" <td>...</td>\n",
- " <td>0.256447</td>\n",
- " <td>0.053749</td>\n",
- " <td>0.134985</td>\n",
- " <td>0.485079</td>\n",
- " <td>0.121168</td>\n",
+ " <td>0.090503</td>\n",
" <td>0.395130</td>\n",
- " <td>0.159200</td>\n",
- " <td>0.111105</td>\n",
- " <td>0.710584</td>\n",
" <td>0.063826</td>\n",
+ " <td>0.165966</td>\n",
+ " <td>0.240338</td>\n",
+ " <td>0.710584</td>\n",
+ " <td>0.159200</td>\n",
+ " <td>0.485079</td>\n",
+ " <td>0.134985</td>\n",
+ " <td>0.381508</td>\n",
" </tr>\n",
" <tr>\n",
" <th>LSTMAD</th>\n",
+ " <td>0.213044</td>\n",
+ " <td>0.669824</td>\n",
+ " <td>0.056562</td>\n",
+ " <td>0.305128</td>\n",
" <td>0.127489</td>\n",
- " <td>0.067250</td>\n",
" <td>0.025419</td>\n",
- " <td>0.133080</td>\n",
- " <td>0.130270</td>\n",
+ " <td>0.329828</td>\n",
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@@ -210,42 +210,42 @@
"</div>"
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"text/plain": [
- " SVDB Power MGAB Daphnet WSD SMAP \\\n",
+ " IOPS SWaT SED MSL SVDB MGAB \\\n",
"Model \n",
- "CNN 0.199785 0.075487 0.006988 0.398456 0.224922 0.336818 \n",
- "IForest 0.307322 0.076373 0.004379 0.518905 0.027487 0.327727 \n",
- "KMeansAD_U 0.811385 0.524166 0.036645 0.039747 0.173060 0.657738 \n",
- "LOF 0.050189 0.090503 0.004639 0.134804 0.102346 0.172499 \n",
- "LSTMAD 0.127489 0.067250 0.025419 0.133080 0.130270 0.273214 \n",
+ "CNN 0.205826 0.680748 0.058416 0.346350 0.199785 0.006988 \n",
+ "IForest 0.134518 0.368230 0.807209 0.448709 0.307322 0.004379 \n",
+ "KMeansAD_U 0.107988 0.111519 0.895291 0.441543 0.811385 0.036645 \n",
+ "LOF 0.123657 0.121168 0.111105 0.186700 0.050189 0.004639 \n",
+ "LSTMAD 0.213044 0.669824 0.056562 0.305128 0.127489 0.025419 \n",
"\n",
- " MSL Exathlon Stock IOPS ... LTDB MITDB \\\n",
+ " LTDB SMAP Daphnet Stock ... Power NEK \\\n",
"Model ... \n",
- "CNN 0.346350 0.657757 0.939925 0.205826 ... 0.406171 0.143632 \n",
- "IForest 0.448709 0.964836 0.735886 0.134518 ... 0.566359 0.159042 \n",
- "KMeansAD_U 0.441543 0.618051 0.738198 0.107988 ... 0.835553 0.590892 \n",
- "LOF 0.186700 0.240338 0.710487 0.123657 ... 0.256447 0.053749 \n",
- "LSTMAD 0.305128 0.735253 0.817960 0.213044 ... 0.329828 0.112398 \n",
+ "CNN 0.406171 0.336818 0.398456 0.939925 ... 0.075487 0.714845 \n",
+ "IForest 0.566359 0.327727 0.518905 0.735886 ... 0.076373 0.649735 \n",
+ "KMeansAD_U 0.835553 0.657738 0.039747 0.738198 ... 0.524166 0.317927 \n",
+ "LOF 0.256447 0.172499 0.134804 0.710487 ... 0.090503 0.395130 \n",
+ "LSTMAD 0.329828 0.273214 0.133080 0.817960 ... 0.067250 0.689697 \n",
"\n",
- " SMD TODS SWaT NEK OPPORTUNITY SED \\\n",
+ " CATSv2 NAB Exathlon TAO OPPORTUNITY TODS \\\n",
"Model \n",
- "CNN 0.545045 0.575941 0.680748 0.714845 0.632799 0.058416 \n",
- "IForest 0.342406 0.487386 0.368230 0.649735 0.736264 0.807209 \n",
- "KMeansAD_U 0.254537 0.739257 0.111519 0.317927 0.351828 0.895291 \n",
- "LOF 0.134985 0.485079 0.121168 0.395130 0.159200 0.111105 \n",
- "LSTMAD 0.483944 0.522228 0.669824 0.689697 0.563772 0.056562 \n",
+ "CNN 0.288293 0.248091 0.657757 0.994270 0.632799 0.575941 \n",
+ "IForest 0.105175 0.342137 0.964836 0.728970 0.736264 0.487386 \n",
+ "KMeansAD_U 0.229268 0.427477 0.618051 0.747945 0.351828 0.739257 \n",
+ "LOF 0.063826 0.165966 0.240338 0.710584 0.159200 0.485079 \n",
+ "LSTMAD 0.329056 0.173732 0.735253 0.995044 0.563772 0.522228 \n",
"\n",
- " TAO CATSv2 \n",
+ " SMD YAHOO \n",
"Model \n",
- "CNN 0.994270 0.288293 \n",
- "IForest 0.728970 0.105175 \n",
- "KMeansAD_U 0.747945 0.229268 \n",
- "LOF 0.710584 0.063826 \n",
- "LSTMAD 0.995044 0.329056 \n",
+ "CNN 0.545045 0.512096 \n",
+ "IForest 0.342406 0.135664 \n",
+ "KMeansAD_U 0.254537 0.781824 \n",
+ "LOF 0.134985 0.381508 \n",
+ "LSTMAD 0.483944 0.417416 \n",
"\n",
"[5 rows x 23 columns]"
]
},
- "execution_count": 6,
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"metadata": {},
"output_type": "execute_result"
}
@@ -262,7 +262,7 @@
},
{
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[
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+ 0.1559495568365849,
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- 0.6294041253579502,
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+ 0.0844371289411118,
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0.928987226092576,
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+ 0.6294041253579502,
+ 0.1923663969249961
]
]
}
@@ -1677,7 +1447,7 @@
}
},
"title": {
- "text": "Oranges Heatmap der VUS-PRvon den einzelnen Modelle auf den jeweiligen Datensätzen"
+ "text": "Oranges Heatmap der VUS-PR von den einzelnen Modelle auf den jeweiligen Datensätzen"
},
"xaxis": {
"title": {
@@ -1711,13 +1481,14 @@
" x= df.columns, \n",
" y= df.index,\n",
" colorscale=scale,#'Viridis',\n",
- " text= df.values,\n",
- " texttemplate=\"%{text:.2f}\",\n",
- " textfont=dict(size=12)\n",
+ " # show values in cells with two digits\n",
+ " # text= df.values,\n",
+ " # texttemplate=\"%{text:.2f}\",\n",
+ " # textfont=dict(size=12)\n",
"))\n",
"\n",
"fig.update_layout(\n",
- " title= scale+' Heatmap der ' +metric+ 'von den einzelnen Modelle auf den jeweiligen Datensätzen',\n",
+ " title= scale+' Heatmap der ' +metric+ ' von den einzelnen Modelle auf den jeweiligen Datensätzen',\n",
" xaxis=dict(title='Datensätze'),\n",
" yaxis=dict(title='Modelle')\n",
")\n",
diff --git a/src/group_evaluation/generate_combined_dataframe.ipynb b/src/group_evaluation/generate_combined_dataframe.ipynb
index 5f18c67cf1fae8dab64de9aca3cbb529b80d59dc..7e41157e859cc470122ec7c14afb287a169d1a11 100644
--- a/src/group_evaluation/generate_combined_dataframe.ipynb
+++ b/src/group_evaluation/generate_combined_dataframe.ipynb
@@ -2,7 +2,7 @@
"cells": [
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
@@ -12,7 +12,7 @@
},
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
@@ -25,7 +25,7 @@
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": 8,
"metadata": {},
"outputs": [
{
@@ -50,26 +50,26 @@
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Model</th>\n",
+ " <th>IOPS</th>\n",
+ " <th>SWaT</th>\n",
+ " <th>SED</th>\n",
+ " <th>MSL</th>\n",
" <th>SVDB</th>\n",
- " <th>Power</th>\n",
" <th>MGAB</th>\n",
- " <th>Daphnet</th>\n",
- " <th>WSD</th>\n",
+ " <th>LTDB</th>\n",
" <th>SMAP</th>\n",
- " <th>MSL</th>\n",
- " <th>Exathlon</th>\n",
- " <th>Stock</th>\n",
+ " <th>Daphnet</th>\n",
" <th>...</th>\n",
- " <th>LTDB</th>\n",
- " <th>MITDB</th>\n",
- " <th>SMD</th>\n",
- " <th>TODS</th>\n",
- " <th>SWaT</th>\n",
+ " <th>Power</th>\n",
" <th>NEK</th>\n",
- " <th>OPPORTUNITY</th>\n",
- " <th>SED</th>\n",
- " <th>TAO</th>\n",
" <th>CATSv2</th>\n",
+ " <th>NAB</th>\n",
+ " <th>Exathlon</th>\n",
+ " <th>TAO</th>\n",
+ " <th>OPPORTUNITY</th>\n",
+ " <th>TODS</th>\n",
+ " <th>SMD</th>\n",
+ " <th>YAHOO</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
@@ -80,13 +80,13 @@
],
"text/plain": [
"Empty DataFrame\n",
- "Columns: [Model, SVDB, Power, MGAB, Daphnet, WSD, SMAP, MSL, Exathlon, Stock, IOPS, UCR, YAHOO, NAB, LTDB, MITDB, SMD, TODS, SWaT, NEK, OPPORTUNITY, SED, TAO, CATSv2]\n",
+ "Columns: [Model, IOPS, SWaT, SED, MSL, SVDB, MGAB, LTDB, SMAP, Daphnet, Stock, WSD, MITDB, UCR, Power, NEK, CATSv2, NAB, Exathlon, TAO, OPPORTUNITY, TODS, SMD, YAHOO]\n",
"Index: []\n",
"\n",
"[0 rows x 24 columns]"
]
},
- "execution_count": 9,
+ "execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
@@ -101,7 +101,7 @@
},
{
"cell_type": "code",
- "execution_count": 10,
+ "execution_count": 9,
"metadata": {},
"outputs": [
{
@@ -117,6 +117,7 @@
"Found: OmniAnomaly.csv\n",
"Found: PCA.csv\n",
"Found: POLY.csv\n",
+ "Found: Sub-LOF.csv\n",
"Found: Sub_KNN.csv\n",
"Not correct file type: temp\n",
"Found: USAD.csv\n",
@@ -125,7 +126,7 @@
}
],
"source": [
- "col = 'AUC-PR'\n",
+ "col = 'VUS-PR'\n",
"\n",
"for file in os.listdir(path):\n",
" suffix = file.split('.')\n",
@@ -157,7 +158,7 @@
},
{
"cell_type": "code",
- "execution_count": 11,
+ "execution_count": 10,
"metadata": {},
"outputs": [
{
@@ -182,148 +183,148 @@
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Model</th>\n",
+ " <th>IOPS</th>\n",
+ " <th>SWaT</th>\n",
+ " <th>SED</th>\n",
+ " <th>MSL</th>\n",
" <th>SVDB</th>\n",
- " <th>Power</th>\n",
" <th>MGAB</th>\n",
- " <th>Daphnet</th>\n",
- " <th>WSD</th>\n",
+ " <th>LTDB</th>\n",
" <th>SMAP</th>\n",
- " <th>MSL</th>\n",
- " <th>Exathlon</th>\n",
- " <th>Stock</th>\n",
+ " <th>Daphnet</th>\n",
" <th>...</th>\n",
- " <th>LTDB</th>\n",
- " <th>MITDB</th>\n",
- " <th>SMD</th>\n",
- " <th>TODS</th>\n",
- " <th>SWaT</th>\n",
+ " <th>Power</th>\n",
" <th>NEK</th>\n",
- " <th>OPPORTUNITY</th>\n",
- " <th>SED</th>\n",
- " <th>TAO</th>\n",
" <th>CATSv2</th>\n",
+ " <th>NAB</th>\n",
+ " <th>Exathlon</th>\n",
+ " <th>TAO</th>\n",
+ " <th>OPPORTUNITY</th>\n",
+ " <th>TODS</th>\n",
+ " <th>SMD</th>\n",
+ " <th>YAHOO</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>CNN</td>\n",
- " <td>0.197103</td>\n",
- " <td>0.072400</td>\n",
- " <td>0.003855</td>\n",
- " <td>0.381499</td>\n",
- " <td>0.303128</td>\n",
- " <td>0.329931</td>\n",
- " <td>0.307033</td>\n",
- " <td>0.654310</td>\n",
- " <td>0.929344</td>\n",
+ " <td>0.205826</td>\n",
+ " <td>0.680748</td>\n",
+ " <td>0.058416</td>\n",
+ " <td>0.346350</td>\n",
+ " <td>0.199785</td>\n",
+ " <td>0.006988</td>\n",
+ " <td>0.406171</td>\n",
+ " <td>0.336818</td>\n",
+ " <td>0.398456</td>\n",
" <td>...</td>\n",
- " <td>0.354462</td>\n",
- " <td>0.160153</td>\n",
- " <td>0.565370</td>\n",
- " <td>0.303786</td>\n",
- " <td>0.738718</td>\n",
- " <td>0.685573</td>\n",
- " <td>0.619160</td>\n",
- " <td>0.029325</td>\n",
- " <td>0.994857</td>\n",
- " <td>0.411894</td>\n",
+ " <td>0.075487</td>\n",
+ " <td>0.714845</td>\n",
+ " <td>0.288293</td>\n",
+ " <td>0.248091</td>\n",
+ " <td>0.657757</td>\n",
+ " <td>0.994270</td>\n",
+ " <td>0.632799</td>\n",
+ " <td>0.575941</td>\n",
+ " <td>0.545045</td>\n",
+ " <td>0.512096</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>IForest</td>\n",
- " <td>0.311936</td>\n",
- " <td>0.073981</td>\n",
- " <td>0.004336</td>\n",
- " <td>0.496579</td>\n",
- " <td>0.040993</td>\n",
- " <td>0.299302</td>\n",
- " <td>0.386085</td>\n",
- " <td>0.962806</td>\n",
- " <td>0.143940</td>\n",
+ " <td>0.134518</td>\n",
+ " <td>0.368230</td>\n",
+ " <td>0.807209</td>\n",
+ " <td>0.448709</td>\n",
+ " <td>0.307322</td>\n",
+ " <td>0.004379</td>\n",
+ " <td>0.566359</td>\n",
+ " <td>0.327727</td>\n",
+ " <td>0.518905</td>\n",
" <td>...</td>\n",
- " <td>0.521341</td>\n",
- " <td>0.169557</td>\n",
- " <td>0.369237</td>\n",
- " <td>0.076521</td>\n",
- " <td>0.702432</td>\n",
- " <td>0.630339</td>\n",
- " <td>0.733153</td>\n",
- " <td>0.691484</td>\n",
- " <td>0.125817</td>\n",
- " <td>0.139416</td>\n",
+ " <td>0.076373</td>\n",
+ " <td>0.649735</td>\n",
+ " <td>0.105175</td>\n",
+ " <td>0.342137</td>\n",
+ " <td>0.964836</td>\n",
+ " <td>0.728970</td>\n",
+ " <td>0.736264</td>\n",
+ " <td>0.487386</td>\n",
+ " <td>0.342406</td>\n",
+ " <td>0.135664</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>KMeansAD_U</td>\n",
- " <td>0.809036</td>\n",
- " <td>0.507629</td>\n",
- " <td>0.085299</td>\n",
- " <td>0.036445</td>\n",
- " <td>0.146372</td>\n",
- " <td>0.648913</td>\n",
- " <td>0.371438</td>\n",
- " <td>0.617690</td>\n",
- " <td>0.114476</td>\n",
+ " <td>0.107988</td>\n",
+ " <td>0.111519</td>\n",
+ " <td>0.895291</td>\n",
+ " <td>0.441543</td>\n",
+ " <td>0.811385</td>\n",
+ " <td>0.036645</td>\n",
+ " <td>0.835553</td>\n",
+ " <td>0.657738</td>\n",
+ " <td>0.039747</td>\n",
" <td>...</td>\n",
- " <td>0.765819</td>\n",
- " <td>0.583808</td>\n",
- " <td>0.260908</td>\n",
- " <td>0.448703</td>\n",
- " <td>0.111152</td>\n",
- " <td>0.346973</td>\n",
- " <td>0.365381</td>\n",
- " <td>0.710575</td>\n",
- " <td>0.129147</td>\n",
- " <td>0.455611</td>\n",
+ " <td>0.524166</td>\n",
+ " <td>0.317927</td>\n",
+ " <td>0.229268</td>\n",
+ " <td>0.427477</td>\n",
+ " <td>0.618051</td>\n",
+ " <td>0.747945</td>\n",
+ " <td>0.351828</td>\n",
+ " <td>0.739257</td>\n",
+ " <td>0.254537</td>\n",
+ " <td>0.781824</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>LOF</td>\n",
- " <td>0.044940</td>\n",
- " <td>0.086245</td>\n",
- " <td>0.002209</td>\n",
- " <td>0.129509</td>\n",
- " <td>0.141918</td>\n",
- " <td>0.180797</td>\n",
- " <td>0.151228</td>\n",
- " <td>0.245106</td>\n",
- " <td>0.112061</td>\n",
+ " <td>0.123657</td>\n",
+ " <td>0.121168</td>\n",
+ " <td>0.111105</td>\n",
+ " <td>0.186700</td>\n",
+ " <td>0.050189</td>\n",
+ " <td>0.004639</td>\n",
+ " <td>0.256447</td>\n",
+ " <td>0.172499</td>\n",
+ " <td>0.134804</td>\n",
" <td>...</td>\n",
- " <td>0.203241</td>\n",
- " <td>0.051628</td>\n",
- " <td>0.182353</td>\n",
- " <td>0.100820</td>\n",
- " <td>0.120683</td>\n",
- " <td>0.363561</td>\n",
- " <td>0.153396</td>\n",
- " <td>0.082198</td>\n",
- " <td>0.167995</td>\n",
- " <td>0.071542</td>\n",
+ " <td>0.090503</td>\n",
+ " <td>0.395130</td>\n",
+ " <td>0.063826</td>\n",
+ " <td>0.165966</td>\n",
+ " <td>0.240338</td>\n",
+ " <td>0.710584</td>\n",
+ " <td>0.159200</td>\n",
+ " <td>0.485079</td>\n",
+ " <td>0.134985</td>\n",
+ " <td>0.381508</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>LSTMAD</td>\n",
- " <td>0.129879</td>\n",
- " <td>0.064788</td>\n",
- " <td>0.045860</td>\n",
- " <td>0.132234</td>\n",
- " <td>0.209492</td>\n",
- " <td>0.278827</td>\n",
- " <td>0.237442</td>\n",
- " <td>0.733875</td>\n",
- " <td>0.519232</td>\n",
+ " <td>0.213044</td>\n",
+ " <td>0.669824</td>\n",
+ " <td>0.056562</td>\n",
+ " <td>0.305128</td>\n",
+ " <td>0.127489</td>\n",
+ " <td>0.025419</td>\n",
+ " <td>0.329828</td>\n",
+ " <td>0.273214</td>\n",
+ " <td>0.133080</td>\n",
" <td>...</td>\n",
- " <td>0.276735</td>\n",
- " <td>0.113066</td>\n",
- " <td>0.539890</td>\n",
- " <td>0.205671</td>\n",
- " <td>0.737695</td>\n",
- " <td>0.667421</td>\n",
- " <td>0.545535</td>\n",
- " <td>0.030497</td>\n",
- " <td>0.993397</td>\n",
- " <td>0.358071</td>\n",
+ " <td>0.067250</td>\n",
+ " <td>0.689697</td>\n",
+ " <td>0.329056</td>\n",
+ " <td>0.173732</td>\n",
+ " <td>0.735253</td>\n",
+ " <td>0.995044</td>\n",
+ " <td>0.563772</td>\n",
+ " <td>0.522228</td>\n",
+ " <td>0.483944</td>\n",
+ " <td>0.417416</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
@@ -331,31 +332,31 @@
"</div>"
],
"text/plain": [
- " Model SVDB Power MGAB Daphnet WSD SMAP \\\n",
- "0 CNN 0.197103 0.072400 0.003855 0.381499 0.303128 0.329931 \n",
- "0 IForest 0.311936 0.073981 0.004336 0.496579 0.040993 0.299302 \n",
- "0 KMeansAD_U 0.809036 0.507629 0.085299 0.036445 0.146372 0.648913 \n",
- "0 LOF 0.044940 0.086245 0.002209 0.129509 0.141918 0.180797 \n",
- "0 LSTMAD 0.129879 0.064788 0.045860 0.132234 0.209492 0.278827 \n",
+ " Model IOPS SWaT SED MSL SVDB MGAB \\\n",
+ "0 CNN 0.205826 0.680748 0.058416 0.346350 0.199785 0.006988 \n",
+ "0 IForest 0.134518 0.368230 0.807209 0.448709 0.307322 0.004379 \n",
+ "0 KMeansAD_U 0.107988 0.111519 0.895291 0.441543 0.811385 0.036645 \n",
+ "0 LOF 0.123657 0.121168 0.111105 0.186700 0.050189 0.004639 \n",
+ "0 LSTMAD 0.213044 0.669824 0.056562 0.305128 0.127489 0.025419 \n",
"\n",
- " MSL Exathlon Stock ... LTDB MITDB SMD TODS \\\n",
- "0 0.307033 0.654310 0.929344 ... 0.354462 0.160153 0.565370 0.303786 \n",
- "0 0.386085 0.962806 0.143940 ... 0.521341 0.169557 0.369237 0.076521 \n",
- "0 0.371438 0.617690 0.114476 ... 0.765819 0.583808 0.260908 0.448703 \n",
- "0 0.151228 0.245106 0.112061 ... 0.203241 0.051628 0.182353 0.100820 \n",
- "0 0.237442 0.733875 0.519232 ... 0.276735 0.113066 0.539890 0.205671 \n",
+ " LTDB SMAP Daphnet ... Power NEK CATSv2 NAB \\\n",
+ "0 0.406171 0.336818 0.398456 ... 0.075487 0.714845 0.288293 0.248091 \n",
+ "0 0.566359 0.327727 0.518905 ... 0.076373 0.649735 0.105175 0.342137 \n",
+ "0 0.835553 0.657738 0.039747 ... 0.524166 0.317927 0.229268 0.427477 \n",
+ "0 0.256447 0.172499 0.134804 ... 0.090503 0.395130 0.063826 0.165966 \n",
+ "0 0.329828 0.273214 0.133080 ... 0.067250 0.689697 0.329056 0.173732 \n",
"\n",
- " SWaT NEK OPPORTUNITY SED TAO CATSv2 \n",
- "0 0.738718 0.685573 0.619160 0.029325 0.994857 0.411894 \n",
- "0 0.702432 0.630339 0.733153 0.691484 0.125817 0.139416 \n",
- "0 0.111152 0.346973 0.365381 0.710575 0.129147 0.455611 \n",
- "0 0.120683 0.363561 0.153396 0.082198 0.167995 0.071542 \n",
- "0 0.737695 0.667421 0.545535 0.030497 0.993397 0.358071 \n",
+ " Exathlon TAO OPPORTUNITY TODS SMD YAHOO \n",
+ "0 0.657757 0.994270 0.632799 0.575941 0.545045 0.512096 \n",
+ "0 0.964836 0.728970 0.736264 0.487386 0.342406 0.135664 \n",
+ "0 0.618051 0.747945 0.351828 0.739257 0.254537 0.781824 \n",
+ "0 0.240338 0.710584 0.159200 0.485079 0.134985 0.381508 \n",
+ "0 0.735253 0.995044 0.563772 0.522228 0.483944 0.417416 \n",
"\n",
"[5 rows x 24 columns]"
]
},
- "execution_count": 11,
+ "execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
@@ -366,11 +367,11 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
- "#df.to_csv(path+'/groupedDataframes/'+col+'_combined_by_group.csv')"
+ "df.to_csv(path+'/groupedDataframes/'+col+'_combined_by_group.csv')"
]
}
],
diff --git a/src/group_evaluation/test.png b/src/group_evaluation/test.png
deleted file mode 100644
index 8ae6e080d9ddc8ed3c358eaf3ca8c231ec9ab01e..0000000000000000000000000000000000000000
Binary files a/src/group_evaluation/test.png and /dev/null differ
diff --git a/src/group_evaluation/test_vus-pr.png b/src/group_evaluation/test_vus-pr.png
deleted file mode 100644
index e32075ae9463b95eb96a85416ab666ea70d5cb03..0000000000000000000000000000000000000000
Binary files a/src/group_evaluation/test_vus-pr.png and /dev/null differ
diff --git a/src/models/desi/USAD.png b/src/models/desi/USAD.png
deleted file mode 100644
index 64f703f3a0c9eba6d618423f5b44367de95a6f12..0000000000000000000000000000000000000000
Binary files a/src/models/desi/USAD.png and /dev/null differ
diff --git a/src/models/desi/desi_evaluate_groups.ipynb b/src/models/desi/desi_evaluate_groups.ipynb
index 3d3ce3cb4b57feb1e4b6a44330642c27c5e69a79..290d7190b578bb5fe9b20177046944a98f58e17c 100644
--- a/src/models/desi/desi_evaluate_groups.ipynb
+++ b/src/models/desi/desi_evaluate_groups.ipynb
@@ -2,7 +2,7 @@
"cells": [
{
"cell_type": "code",
- "execution_count": 19,
+ "execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
@@ -13,7 +13,7 @@
},
{
"cell_type": "code",
- "execution_count": 36,
+ "execution_count": 164,
"metadata": {},
"outputs": [
{
@@ -59,146 +59,153 @@
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
- " <td>{'n_neighbors': 30}</td>\n",
+ " <td>{'periodicity': 3, 'n_neighbors': 10}</td>\n",
" <td>001_NAB_id_1_Facility_tr_1007_1st_2014.csv</td>\n",
- " <td>0.662725</td>\n",
+ " <td>0.653164</td>\n",
" <td>NAB</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
- " <td>0.140581</td>\n",
- " <td>0.511654</td>\n",
- " <td>0.139685</td>\n",
- " <td>0.517581</td>\n",
- " <td>0.158465</td>\n",
+ " <td>0.321899</td>\n",
+ " <td>0.608477</td>\n",
+ " <td>0.316988</td>\n",
+ " <td>0.611647</td>\n",
+ " <td>0.342408</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
- " <td>0.360914</td>\n",
- " <td>0.968482</td>\n",
- " <td>0.034985</td>\n",
- " <td>0.923077</td>\n",
+ " <td>0.642756</td>\n",
+ " <td>0.964006</td>\n",
+ " <td>0.119534</td>\n",
+ " <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
- " <td>{'n_neighbors': 50}</td>\n",
+ " <td>{'periodicity': 1, 'n_neighbors': 50}</td>\n",
" <td>002_NAB_id_2_WebService_tr_1500_1st_4106.csv</td>\n",
- " <td>1.600371</td>\n",
+ " <td>1.806566</td>\n",
" <td>NAB</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
- " <td>0.136906</td>\n",
- " <td>0.514480</td>\n",
- " <td>0.139172</td>\n",
- " <td>0.522671</td>\n",
- " <td>0.192924</td>\n",
+ " <td>0.532093</td>\n",
+ " <td>0.582393</td>\n",
+ " <td>0.538952</td>\n",
+ " <td>0.616685</td>\n",
+ " <td>0.637707</td>\n",
+ " <td>1.000000</td>\n",
" <td>1.000000</td>\n",
+ " <td>0.530904</td>\n",
+ " <td>0.995618</td>\n",
+ " <td>0.270016</td>\n",
" <td>1.000000</td>\n",
- " <td>0.336815</td>\n",
- " <td>0.988203</td>\n",
- " <td>0.032967</td>\n",
- " <td>0.567568</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
- " <td>{'n_neighbors': 40}</td>\n",
+ " <td>{'periodicity': 3, 'n_neighbors': 40}</td>\n",
" <td>003_NAB_id_3_WebService_tr_1362_1st_1462.csv</td>\n",
- " <td>2.794641</td>\n",
+ " <td>2.038316</td>\n",
" <td>NAB</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
- " <td>0.108531</td>\n",
- " <td>0.508964</td>\n",
- " <td>0.097869</td>\n",
- " <td>0.500551</td>\n",
- " <td>0.175308</td>\n",
- " <td>0.999672</td>\n",
- " <td>0.933333</td>\n",
- " <td>0.327012</td>\n",
- " <td>0.945860</td>\n",
- " <td>0.014445</td>\n",
- " <td>0.666667</td>\n",
+ " <td>0.134022</td>\n",
+ " <td>0.522890</td>\n",
+ " <td>0.139534</td>\n",
+ " <td>0.529691</td>\n",
+ " <td>0.190514</td>\n",
+ " <td>0.939543</td>\n",
+ " <td>0.244131</td>\n",
+ " <td>0.151951</td>\n",
+ " <td>0.682496</td>\n",
+ " <td>0.016415</td>\n",
+ " <td>0.126263</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
- " <td>{'n_neighbors': 50}</td>\n",
+ " <td>{'periodicity': 3, 'n_neighbors': 50}</td>\n",
" <td>004_NAB_id_4_Facility_tr_1007_1st_1437.csv</td>\n",
- " <td>0.889990</td>\n",
+ " <td>0.926782</td>\n",
" <td>NAB</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
- " <td>0.157897</td>\n",
- " <td>0.541035</td>\n",
- " <td>0.153577</td>\n",
- " <td>0.556081</td>\n",
- " <td>0.186381</td>\n",
+ " <td>0.515828</td>\n",
+ " <td>0.788997</td>\n",
+ " <td>0.520351</td>\n",
+ " <td>0.804107</td>\n",
+ " <td>0.508470</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
- " <td>0.338843</td>\n",
- " <td>0.980346</td>\n",
- " <td>0.007463</td>\n",
+ " <td>0.627049</td>\n",
+ " <td>0.988360</td>\n",
+ " <td>0.310945</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
- " <td>{'n_neighbors': 40}</td>\n",
+ " <td>{'periodicity': 1, 'n_neighbors': 50}</td>\n",
" <td>005_NAB_id_5_Traffic_tr_594_1st_1645.csv</td>\n",
- " <td>0.661092</td>\n",
+ " <td>0.726600</td>\n",
" <td>NAB</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
- " <td>0.103901</td>\n",
- " <td>0.498313</td>\n",
- " <td>0.106037</td>\n",
- " <td>0.507622</td>\n",
- " <td>0.185677</td>\n",
- " <td>0.942574</td>\n",
- " <td>0.216216</td>\n",
- " <td>0.194903</td>\n",
- " <td>0.670264</td>\n",
- " <td>0.016807</td>\n",
- " <td>0.121212</td>\n",
+ " <td>0.074486</td>\n",
+ " <td>0.369671</td>\n",
+ " <td>0.077129</td>\n",
+ " <td>0.382665</td>\n",
+ " <td>0.181886</td>\n",
+ " <td>0.810903</td>\n",
+ " <td>0.181262</td>\n",
+ " <td>0.435004</td>\n",
+ " <td>0.670916</td>\n",
+ " <td>0.000000</td>\n",
+ " <td>0.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
- " params file_name \\\n",
- "0 {'n_neighbors': 30} 001_NAB_id_1_Facility_tr_1007_1st_2014.csv \n",
- "1 {'n_neighbors': 50} 002_NAB_id_2_WebService_tr_1500_1st_4106.csv \n",
- "2 {'n_neighbors': 40} 003_NAB_id_3_WebService_tr_1362_1st_1462.csv \n",
- "3 {'n_neighbors': 50} 004_NAB_id_4_Facility_tr_1007_1st_1437.csv \n",
- "4 {'n_neighbors': 40} 005_NAB_id_5_Traffic_tr_594_1st_1645.csv \n",
+ " params \\\n",
+ "0 {'periodicity': 3, 'n_neighbors': 10} \n",
+ "1 {'periodicity': 1, 'n_neighbors': 50} \n",
+ "2 {'periodicity': 3, 'n_neighbors': 40} \n",
+ "3 {'periodicity': 3, 'n_neighbors': 50} \n",
+ "4 {'periodicity': 1, 'n_neighbors': 50} \n",
"\n",
- " duration group point anomaly seq anomaly AUC-PR AUC-ROC VUS-PR \\\n",
- "0 0.662725 NAB False True 0.140581 0.511654 0.139685 \n",
- "1 1.600371 NAB False False 0.136906 0.514480 0.139172 \n",
- "2 2.794641 NAB False True 0.108531 0.508964 0.097869 \n",
- "3 0.889990 NAB False False 0.157897 0.541035 0.153577 \n",
- "4 0.661092 NAB False False 0.103901 0.498313 0.106037 \n",
+ " file_name duration group \\\n",
+ "0 001_NAB_id_1_Facility_tr_1007_1st_2014.csv 0.653164 NAB \n",
+ "1 002_NAB_id_2_WebService_tr_1500_1st_4106.csv 1.806566 NAB \n",
+ "2 003_NAB_id_3_WebService_tr_1362_1st_1462.csv 2.038316 NAB \n",
+ "3 004_NAB_id_4_Facility_tr_1007_1st_1437.csv 0.926782 NAB \n",
+ "4 005_NAB_id_5_Traffic_tr_594_1st_1645.csv 0.726600 NAB \n",
"\n",
- " VUS-ROC Standard-F1 PA-F1 Event-based-F1 R-based-F1 Affiliation-F \\\n",
- "0 0.517581 0.158465 1.000000 1.000000 0.360914 0.968482 \n",
- "1 0.522671 0.192924 1.000000 1.000000 0.336815 0.988203 \n",
- "2 0.500551 0.175308 0.999672 0.933333 0.327012 0.945860 \n",
- "3 0.556081 0.186381 1.000000 1.000000 0.338843 0.980346 \n",
- "4 0.507622 0.185677 0.942574 0.216216 0.194903 0.670264 \n",
+ " point anomaly seq anomaly AUC-PR AUC-ROC VUS-PR VUS-ROC \\\n",
+ "0 False True 0.321899 0.608477 0.316988 0.611647 \n",
+ "1 False False 0.532093 0.582393 0.538952 0.616685 \n",
+ "2 False True 0.134022 0.522890 0.139534 0.529691 \n",
+ "3 False False 0.515828 0.788997 0.520351 0.804107 \n",
+ "4 False False 0.074486 0.369671 0.077129 0.382665 \n",
"\n",
- " Recall Precision \n",
- "0 0.034985 0.923077 \n",
- "1 0.032967 0.567568 \n",
- "2 0.014445 0.666667 \n",
- "3 0.007463 1.000000 \n",
- "4 0.016807 0.121212 "
+ " Standard-F1 PA-F1 Event-based-F1 R-based-F1 Affiliation-F Recall \\\n",
+ "0 0.342408 1.000000 1.000000 0.642756 0.964006 0.119534 \n",
+ "1 0.637707 1.000000 1.000000 0.530904 0.995618 0.270016 \n",
+ "2 0.190514 0.939543 0.244131 0.151951 0.682496 0.016415 \n",
+ "3 0.508470 1.000000 1.000000 0.627049 0.988360 0.310945 \n",
+ "4 0.181886 0.810903 0.181262 0.435004 0.670916 0.000000 \n",
+ "\n",
+ " Precision \n",
+ "0 1.000000 \n",
+ "1 1.000000 \n",
+ "2 0.126263 \n",
+ "3 1.000000 \n",
+ "4 0.000000 "
]
},
- "execution_count": 36,
+ "execution_count": 164,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#Dataframe erstellen\n",
- "model = 'LOF'\n",
+ "model = 'Sub-LOF'\n",
"path = '../../../docs/evaluation/'+model+'.csv'\n",
"df = pd.read_csv(path)\n",
"df.head()\n",
@@ -207,7 +214,7 @@
},
{
"cell_type": "code",
- "execution_count": 37,
+ "execution_count": 165,
"metadata": {},
"outputs": [
{
@@ -240,7 +247,7 @@
"Name: count, dtype: int64"
]
},
- "execution_count": 37,
+ "execution_count": 165,
"metadata": {},
"output_type": "execute_result"
}
@@ -251,7 +258,7 @@
},
{
"cell_type": "code",
- "execution_count": 38,
+ "execution_count": 166,
"metadata": {},
"outputs": [],
"source": [
@@ -291,7 +298,7 @@
},
{
"cell_type": "code",
- "execution_count": 39,
+ "execution_count": 180,
"metadata": {},
"outputs": [
{
@@ -387,34 +394,34 @@
"x0": " ",
"xaxis": "x",
"y": [
- 0.1396847903332389,
- 0.139172125084749,
- 0.0978688395614442,
- 0.1535768761124069,
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+ 0.3169875495098878,
+ 0.5389522106420179,
+ 0.1395342293514921,
+ 0.5203509865769482,
+ 0.0771290722029058,
+ 0.7728834814108334,
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+ 0.6622429485202322,
+ 0.2247391151580552,
+ 0.858911151071202,
+ 0.5400073594712449,
+ 0.6239283218730405,
+ 0.9651481667941308,
+ 0.6437255332120525,
+ 0.633537837894686,
+ 0.1866206050735881,
+ 0.5998317717124477,
+ 0.3326922242606973,
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+ 0.6468153250078241,
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+ 0.122260710435827,
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+ 0.1308934252292885,
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+ 0.6238487174589644,
+ 0.9745167111318188
],
"y0": " ",
"yaxis": "y"
@@ -489,31 +496,31 @@
"x0": " ",
"xaxis": "x",
"y": [
- 0.0777231681031569,
- 0.0788657664187751,
- 0.2826024087267116,
- 0.2391140920137143,
- 0.1337393597657766,
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- 0.0049874770243891,
- 0.0359509423387786,
- 0.0784886813207732,
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}
},
"title": {
- "text": "<b> Vergleich der Metriken zwischen den Gruppen für LOF </b>",
+ "text": "<b> Vergleich der Metriken zwischen den Gruppen für Sub-LOF </b>",
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},
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" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
- " <td>{'n_neighbors': 30}</td>\n",
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" <td>001_NAB_id_1_Facility_tr_1007_1st_2014.csv</td>\n",
- " <td>0.662725</td>\n",
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" <td>Sequenzeanomalie</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
- " <td>{'n_neighbors': 40}</td>\n",
+ " <td>{'periodicity': 3, 'n_neighbors': 40}</td>\n",
" <td>003_NAB_id_3_WebService_tr_1362_1st_1462.csv</td>\n",
- " <td>2.794641</td>\n",
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" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
- " <td>{'n_neighbors': 50}</td>\n",
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" <td>006_NAB_id_6_Traffic_tr_2579_1st_5839.csv</td>\n",
- " <td>3.211013</td>\n",
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" <td>NAB</td>\n",
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" <th>6</th>\n",
- " <td>{'n_neighbors': 50}</td>\n",
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" <td>007_NAB_id_7_Traffic_tr_624_1st_2087.csv</td>\n",
- " <td>1.559115</td>\n",
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" <td>Sequenzeanomalie</td>\n",
" </tr>\n",
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" <th>9</th>\n",
- " <td>{'n_neighbors': 20}</td>\n",
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" <td>010_NAB_id_10_WebService_tr_500_1st_271.csv</td>\n",
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"</div>"
],
"text/plain": [
- " params file_name \\\n",
- "0 {'n_neighbors': 30} 001_NAB_id_1_Facility_tr_1007_1st_2014.csv \n",
- "2 {'n_neighbors': 40} 003_NAB_id_3_WebService_tr_1362_1st_1462.csv \n",
- "5 {'n_neighbors': 50} 006_NAB_id_6_Traffic_tr_2579_1st_5839.csv \n",
- "6 {'n_neighbors': 50} 007_NAB_id_7_Traffic_tr_624_1st_2087.csv \n",
- "9 {'n_neighbors': 20} 010_NAB_id_10_WebService_tr_500_1st_271.csv \n",
+ " params \\\n",
+ "0 {'periodicity': 3, 'n_neighbors': 10} \n",
+ "2 {'periodicity': 3, 'n_neighbors': 40} \n",
+ "5 {'periodicity': 1, 'n_neighbors': 50} \n",
+ "6 {'periodicity': 1, 'n_neighbors': 50} \n",
+ "9 {'periodicity': 3, 'n_neighbors': 40} \n",
"\n",
- " duration group point anomaly seq anomaly AUC-PR AUC-ROC VUS-PR \\\n",
- "0 0.662725 NAB False True 0.140581 0.511654 0.139685 \n",
- "2 2.794641 NAB False True 0.108531 0.508964 0.097869 \n",
- "5 3.211013 NAB False True 0.139686 0.515552 0.155340 \n",
- "6 1.559115 NAB False True 0.170066 0.547980 0.219652 \n",
- "9 1.627614 NAB False True 0.223609 0.556116 0.342451 \n",
+ " file_name duration group point anomaly \\\n",
+ "0 001_NAB_id_1_Facility_tr_1007_1st_2014.csv 0.653164 NAB False \n",
+ "2 003_NAB_id_3_WebService_tr_1362_1st_1462.csv 2.038316 NAB False \n",
+ "5 006_NAB_id_6_Traffic_tr_2579_1st_5839.csv 3.487413 NAB False \n",
+ "6 007_NAB_id_7_Traffic_tr_624_1st_2087.csv 1.600060 NAB False \n",
+ "9 010_NAB_id_10_WebService_tr_500_1st_271.csv 1.628332 NAB False \n",
"\n",
- " VUS-ROC Standard-F1 PA-F1 Event-based-F1 R-based-F1 Affiliation-F \\\n",
- "0 0.517581 0.158465 1.000000 1.000000 0.360914 0.968482 \n",
- "2 0.500551 0.175308 0.999672 0.933333 0.327012 0.945860 \n",
- "5 0.589865 0.182108 0.884120 0.780488 0.472986 0.824601 \n",
- "6 0.663251 0.190288 0.997988 0.916667 0.330642 0.927725 \n",
- "9 0.748768 0.272985 1.000000 1.000000 0.369861 0.965715 \n",
+ " seq anomaly AUC-PR AUC-ROC VUS-PR VUS-ROC Standard-F1 PA-F1 \\\n",
+ "0 True 0.321899 0.608477 0.316988 0.611647 0.342408 1.000000 \n",
+ "2 True 0.134022 0.522890 0.139534 0.529691 0.190514 0.939543 \n",
+ "5 True 0.745636 0.939573 0.772883 0.969517 0.715239 0.961269 \n",
+ "6 True 0.859281 0.988414 0.942440 0.995564 0.918514 1.000000 \n",
+ "9 True 0.601735 0.909585 0.858911 0.962755 0.656315 0.655738 \n",
"\n",
- " Recall Precision anomaly \n",
- "0 0.034985 0.923077 Sequenzeanomalie \n",
- "2 0.014445 0.666667 Sequenzeanomalie \n",
- "5 0.031068 0.761905 Sequenzeanomalie \n",
- "6 0.060484 0.535714 Sequenzeanomalie \n",
- "9 0.040541 0.545455 Sequenzeanomalie "
+ " Event-based-F1 R-based-F1 Affiliation-F Recall Precision \\\n",
+ "0 1.000000 0.642756 0.964006 0.119534 1.000000 \n",
+ "2 0.244131 0.151951 0.682496 0.016415 0.126263 \n",
+ "5 0.908084 0.580197 0.911285 0.245631 0.910072 \n",
+ "6 1.000000 0.927008 0.952722 0.141129 1.000000 \n",
+ "9 0.654867 0.566628 0.939757 0.000000 0.000000 \n",
+ "\n",
+ " anomaly \n",
+ "0 Sequenzeanomalie \n",
+ "2 Sequenzeanomalie \n",
+ "5 Sequenzeanomalie \n",
+ "6 Sequenzeanomalie \n",
+ "9 Sequenzeanomalie "
]
},
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}
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}
},
"title": {
- "text": "<b> Vergleich der Ergebnisse der Anomalien zwischen den Gruppen für LOF </b>",
+ "text": "<b> Vergleich der Ergebnisse der Anomalien zwischen den Gruppen für Sub-LOF </b>",
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],
"source": [
"#Boxplot for anomalies\n",
- "metric = 'VUS-PR'\n",
"fig = px.box(df_anomaly, x = 'anomaly',y=metric, color='group',color_discrete_map= colors,hover_name=\"group\", hover_data=[\"group\"])\n",
"fig.update_layout( \n",
" template = 'ggplot2',\n",
@@ -5459,90 +5472,90 @@
},
{
"cell_type": "code",
- "execution_count": 42,
+ "execution_count": 183,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- " duration AUC-PR AUC-ROC VUS-PR VUS-ROC Standard-F1 \\\n",
- "group \n",
- "CATSv2 47.136594 0.071542 0.508872 0.063826 0.532996 0.094029 \n",
- "Daphnet 5.897125 0.129509 0.570455 0.134804 0.584871 0.290327 \n",
- "Exathlon 7.824180 0.245106 0.571639 0.240338 0.569108 0.388745 \n",
- "IOPS 18.836056 0.116787 0.629300 0.123657 0.718189 0.241223 \n",
- "LTDB 48.170647 0.203241 0.508966 0.256447 0.535053 0.312078 \n",
- "MGAB 17.135755 0.002209 0.507583 0.004639 0.698543 0.009506 \n",
- "MITDB 187.733897 0.051628 0.508271 0.053749 0.503163 0.099617 \n",
- "MSL 1.521115 0.151228 0.559967 0.186700 0.640386 0.202279 \n",
- "NAB 1.595559 0.144844 0.524467 0.165966 0.567408 0.205497 \n",
- "NEK 0.659403 0.363561 0.668191 0.395130 0.742972 0.427307 \n",
- "OPPORTUNITY 2.282972 0.153396 0.612566 0.159200 0.628705 0.266409 \n",
- "Power 5.743324 0.086245 0.495163 0.090503 0.510731 0.162795 \n",
- "SED 7.071819 0.082198 0.548027 0.111105 0.711726 0.142807 \n",
- "SMAP 1.431995 0.180797 0.581760 0.172499 0.592502 0.231062 \n",
- "SMD 3.190204 0.182353 0.632759 0.134985 0.667491 0.325650 \n",
- "SVDB 35.201644 0.044940 0.512603 0.050189 0.523976 0.087034 \n",
- "SWaT 95.530155 0.120683 0.500025 0.121168 0.500155 0.215281 \n",
- "Stock 108.318561 0.112061 0.530383 0.710487 0.904106 0.304437 \n",
- "TAO 24.947558 0.167995 0.449091 0.710584 0.840461 0.230177 \n",
- "TODS 8.166461 0.100820 0.536789 0.485079 0.863128 0.168044 \n",
- "UCR 28.145674 0.048985 0.606013 0.051489 0.706580 0.092895 \n",
- "WSD 2.635757 0.141918 0.638387 0.102346 0.777776 0.225878 \n",
- "YAHOO 0.825724 0.409909 0.828505 0.381508 0.927479 0.443120 \n",
+ " duration AUC-PR AUC-ROC VUS-PR VUS-ROC Standard-F1 \\\n",
+ "group \n",
+ "CATSv2 298.530087 0.511976 0.740398 0.393045 0.760152 0.575803 \n",
+ "Daphnet 6.632036 0.252282 0.905126 0.253956 0.899824 0.406682 \n",
+ "Exathlon 9.833754 0.257618 0.647576 0.262478 0.653360 0.371983 \n",
+ "IOPS 40.815497 0.263492 0.852975 0.380817 0.892852 0.350879 \n",
+ "LTDB 72.072497 0.333160 0.627012 0.409530 0.712029 0.398966 \n",
+ "MGAB 14.901103 0.567335 0.987331 0.634748 0.995269 0.671333 \n",
+ "MITDB 1327.810889 0.385195 0.760688 0.367125 0.827341 0.431379 \n",
+ "MSL 1.503881 0.442670 0.879267 0.544711 0.922678 0.555176 \n",
+ "NAB 1.629958 0.495381 0.730109 0.532450 0.761626 0.544592 \n",
+ "NEK 0.625705 0.554506 0.863816 0.687020 0.911436 0.655181 \n",
+ "OPPORTUNITY 2.531083 0.158653 0.437972 0.149548 0.452675 0.230552 \n",
+ "Power 7.826579 0.175035 0.552633 0.160858 0.573030 0.211897 \n",
+ "SED 7.801529 0.109660 0.605685 0.253420 0.793686 0.216518 \n",
+ "SMAP 1.376011 0.510341 0.828578 0.597854 0.863763 0.595748 \n",
+ "SMD 3.926767 0.486307 0.857014 0.544696 0.868968 0.565768 \n",
+ "SVDB 87.218147 0.356140 0.720499 0.383000 0.776552 0.422369 \n",
+ "SWaT 183.587712 0.113563 0.375616 0.113915 0.377762 0.220540 \n",
+ "Stock 79.056635 0.115033 0.600040 0.747567 0.889482 0.190880 \n",
+ "TAO 39.657654 0.139803 0.612240 0.807694 0.892831 0.223327 \n",
+ "TODS 7.598674 0.166507 0.676933 0.691125 0.887259 0.270928 \n",
+ "UCR 31.333646 0.495182 0.917224 0.514326 0.946238 0.551956 \n",
+ "WSD 3.365790 0.539254 0.959885 0.551041 0.977565 0.594305 \n",
+ "YAHOO 0.776184 0.150503 0.916171 0.451001 0.930039 0.237975 \n",
"\n",
" PA-F1 Event-based-F1 R-based-F1 Affiliation-F Recall \\\n",
"group \n",
- "CATSv2 0.960104 0.478827 0.188141 0.727454 0.010473 \n",
- "Daphnet 0.980234 0.468354 0.394045 0.798326 0.032090 \n",
- "Exathlon 0.840527 0.678066 0.378081 0.857433 0.027732 \n",
- "IOPS 0.566742 0.359596 0.203257 0.734568 0.092212 \n",
- "LTDB 0.570894 0.420305 0.178030 0.740034 0.004915 \n",
- "MGAB 0.142064 0.020381 0.015286 0.680741 0.023254 \n",
- "MITDB 0.204093 0.103453 0.157732 0.698034 0.000314 \n",
- "MSL 0.863703 0.681253 0.289638 0.879443 0.033586 \n",
- "NAB 0.931362 0.716711 0.289656 0.875051 0.026457 \n",
- "NEK 0.899675 0.851266 0.443166 0.922867 0.168942 \n",
- "OPPORTUNITY 0.647512 0.486989 0.209339 0.823082 0.029277 \n",
- "Power 0.959846 0.171831 0.122386 0.700485 0.009333 \n",
- "SED 0.272876 0.272876 0.074110 0.669564 0.006529 \n",
- "SMAP 0.741028 0.585398 0.297406 0.830543 0.135259 \n",
- "SMD 0.820056 0.640711 0.280492 0.866248 0.109229 \n",
- "SVDB 0.660353 0.261395 0.155431 0.711470 0.006957 \n",
- "SWaT 0.849009 0.177778 0.042904 0.297959 0.000158 \n",
- "Stock 0.153897 0.153896 0.042597 0.677526 0.000000 \n",
- "TAO 0.192544 0.185428 0.097249 0.679254 0.022038 \n",
- "TODS 0.531769 0.223785 0.219245 0.688507 0.027175 \n",
- "UCR 0.547013 0.196440 0.093627 0.784911 0.142430 \n",
- "WSD 0.792634 0.766117 0.359934 0.899346 0.153504 \n",
- "YAHOO 0.492777 0.469794 0.446144 0.809881 0.448921 \n",
+ "CATSv2 0.674950 0.575705 0.232829 0.751034 0.310946 \n",
+ "Daphnet 0.666667 0.420230 0.322369 0.830045 0.117953 \n",
+ "Exathlon 0.800635 0.526162 0.317170 0.804928 0.041724 \n",
+ "IOPS 0.620676 0.387128 0.365823 0.877418 0.356618 \n",
+ "LTDB 0.678791 0.522393 0.319594 0.789237 0.065606 \n",
+ "MGAB 0.712791 0.688846 0.689193 0.960863 0.775952 \n",
+ "MITDB 0.823174 0.687269 0.361808 0.907308 0.267250 \n",
+ "MSL 0.918910 0.757484 0.478641 0.934923 0.289677 \n",
+ "NAB 0.954451 0.885003 0.529483 0.939654 0.148962 \n",
+ "NEK 0.876030 0.783539 0.670862 0.953170 0.246789 \n",
+ "OPPORTUNITY 0.938092 0.823990 0.316216 0.927716 0.123624 \n",
+ "Power 0.913381 0.519774 0.290669 0.782209 0.096000 \n",
+ "SED 0.307548 0.219303 0.070964 0.835491 0.082465 \n",
+ "SMAP 0.842265 0.737461 0.535060 0.965606 0.524001 \n",
+ "SMD 0.838555 0.715433 0.487338 0.936624 0.569888 \n",
+ "SVDB 0.815126 0.696453 0.372470 0.913591 0.320710 \n",
+ "SWaT 0.963075 0.295203 0.095314 0.705366 0.009042 \n",
+ "Stock 0.171946 0.170557 0.114896 0.677843 0.004799 \n",
+ "TAO 0.224187 0.221474 0.232479 0.681972 0.017645 \n",
+ "TODS 0.414800 0.246763 0.247089 0.752759 0.058744 \n",
+ "UCR 0.804651 0.709924 0.505175 0.943542 0.761255 \n",
+ "WSD 0.718254 0.672151 0.612024 0.973103 0.798756 \n",
+ "YAHOO 0.238365 0.219175 0.251613 0.912850 0.564290 \n",
"\n",
" Precision \n",
"group \n",
- "CATSv2 0.895954 \n",
- "Daphnet 0.305785 \n",
- "Exathlon 0.512979 \n",
- "IOPS 0.190090 \n",
- "LTDB 0.265047 \n",
- "MGAB 0.003402 \n",
- "MITDB 0.112437 \n",
- "MSL 0.644011 \n",
- "NAB 0.456076 \n",
- "NEK 0.739188 \n",
- "OPPORTUNITY 0.293842 \n",
- "Power 0.061674 \n",
- "SED 1.000000 \n",
- "SMAP 0.492777 \n",
- "SMD 0.454227 \n",
- "SVDB 0.240425 \n",
- "SWaT 0.242424 \n",
- "Stock 0.000000 \n",
- "TAO 0.666667 \n",
- "TODS 0.141732 \n",
- "UCR 0.071834 \n",
- "WSD 0.331186 \n",
- "YAHOO 0.295807 \n"
+ "CATSv2 0.952401 \n",
+ "Daphnet 0.407186 \n",
+ "Exathlon 0.268818 \n",
+ "IOPS 0.232859 \n",
+ "LTDB 0.528795 \n",
+ "MGAB 0.555421 \n",
+ "MITDB 0.506898 \n",
+ "MSL 0.468071 \n",
+ "NAB 0.637919 \n",
+ "NEK 0.611677 \n",
+ "OPPORTUNITY 0.407288 \n",
+ "Power 0.362720 \n",
+ "SED 0.173993 \n",
+ "SMAP 0.511394 \n",
+ "SMD 0.423607 \n",
+ "SVDB 0.529825 \n",
+ "SWaT 0.055148 \n",
+ "Stock 0.191968 \n",
+ "TAO 0.224967 \n",
+ "TODS 0.205223 \n",
+ "UCR 0.238402 \n",
+ "WSD 0.265358 \n",
+ "YAHOO 0.068880 \n"
]
}
],
@@ -5555,15 +5568,15 @@
},
{
"cell_type": "code",
- "execution_count": 43,
+ "execution_count": 184,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "Gesamtdauer Training in s: 7330.821, in min: 122.180, in h: 2.036\n",
- "Durchschnittliches Training pro Datei in s: 18.466\n"
+ "Gesamtdauer Training in s: 18505.362, in min: 308.423, in h: 5.140\n",
+ "Durchschnittliches Training pro Datei in s: 46.613\n"
]
}
],
@@ -5582,15 +5595,15 @@
},
{
"cell_type": "code",
- "execution_count": 44,
+ "execution_count": 185,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "Durchschnittle Gesamt-Performanz des Modells: LOF\n",
- "Recall: 0.111, Precision: 0.304, F1: 0.235, Auc-Roc: 0.604, Auc-PR: 0.156, Vus-PR: 0.185\n"
+ "Durchschnittle Gesamt-Performanz des Modells: Sub-LOF\n",
+ "Recall: 0.420, Precision: 0.345, F1: 0.450, Auc-Roc: 0.794, Auc-PR: 0.374, Vus-PR: 0.473\n"
]
}
],
@@ -5609,7 +5622,7 @@
},
{
"cell_type": "code",
- "execution_count": 45,
+ "execution_count": 186,
"metadata": {},
"outputs": [
{
@@ -5617,8 +5630,8 @@
"output_type": "stream",
"text": [
"Anzahl an Datensätzen mit Punktanomalien: 55\n",
- "Durchschnittle Gesamt-Performanz des Modells: LOF\n",
- "Recall: 0.317, Precision: 0.166, F1: 0.333, Auc-Roc: 0.724, Auc-PR: 0.274, Vus-PR: 0.416\n"
+ "Durchschnittle Gesamt-Performanz des Modells: Sub-LOF\n",
+ "Recall: 0.433, Precision: 0.077, F1: 0.207, Auc-Roc: 0.831, Auc-PR: 0.131, Vus-PR: 0.514\n"
]
}
],
@@ -5640,42 +5653,42 @@
},
{
"cell_type": "code",
- "execution_count": 46,
+ "execution_count": 187,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- " duration AUC-PR AUC-ROC VUS-PR VUS-ROC Standard-F1 \\\n",
- "group \n",
- "IOPS 4.113908 0.176712 0.663981 0.073159 0.740973 0.264796 \n",
- "Stock 108.318561 0.112061 0.530383 0.710487 0.904106 0.304437 \n",
- "TAO 23.744251 0.128972 0.438938 0.623702 0.779843 0.218371 \n",
- "TODS 11.304390 0.071959 0.487086 0.786747 0.960999 0.139983 \n",
- "UCR 13.370526 0.000653 0.661867 0.012963 0.941590 0.001303 \n",
- "WSD 2.101602 0.003879 0.695177 0.035113 0.824391 0.025333 \n",
- "YAHOO 0.850327 0.422520 0.843186 0.383203 0.949400 0.445450 \n",
+ " duration AUC-PR AUC-ROC VUS-PR VUS-ROC Standard-F1 \\\n",
+ "group \n",
+ "IOPS 12.568524 0.121683 0.752821 0.327754 0.766857 0.305542 \n",
+ "Stock 79.056635 0.115033 0.600040 0.747567 0.889482 0.190880 \n",
+ "TAO 39.720064 0.145212 0.623099 0.755775 0.865220 0.234609 \n",
+ "TODS 11.743374 0.077775 0.576626 0.849582 0.910985 0.123648 \n",
+ "UCR 45.350693 0.040927 0.712320 0.208122 0.944659 0.073704 \n",
+ "WSD 2.786840 0.327958 0.970473 0.140331 0.971781 0.317294 \n",
+ "YAHOO 0.800434 0.141987 0.958061 0.475296 0.973913 0.226614 \n",
"\n",
" PA-F1 Event-based-F1 R-based-F1 Affiliation-F Recall \\\n",
"group \n",
- "IOPS 0.998330 0.750000 0.380944 0.862706 0.168886 \n",
- "Stock 0.153897 0.153896 0.042597 0.677526 0.000000 \n",
- "TAO 0.168078 0.168078 0.044159 0.679741 0.001087 \n",
- "TODS 0.108607 0.106481 0.042489 0.671435 0.000000 \n",
- "UCR 0.001219 0.001219 0.001560 0.737802 0.400000 \n",
- "WSD 0.028900 0.010430 0.014322 0.718439 0.083333 \n",
- "YAHOO 0.441885 0.441885 0.448546 0.809781 0.481720 \n",
+ "IOPS 0.573289 0.060249 0.089617 0.899868 0.250555 \n",
+ "Stock 0.171946 0.170557 0.114896 0.677843 0.004799 \n",
+ "TAO 0.235108 0.233242 0.269589 0.683937 0.019654 \n",
+ "TODS 0.123579 0.121521 0.169499 0.671932 0.006386 \n",
+ "UCR 0.073547 0.073547 0.089822 0.837652 0.600000 \n",
+ "WSD 0.357784 0.312380 0.325541 0.853444 0.500000 \n",
+ "YAHOO 0.195229 0.192963 0.246578 0.923807 0.620430 \n",
"\n",
" Precision \n",
"group \n",
- "IOPS 0.025308 \n",
- "Stock 0.000000 \n",
- "TAO 0.500000 \n",
- "TODS 0.000000 \n",
- "UCR 0.000321 \n",
- "WSD 0.001149 \n",
- "YAHOO 0.259860 \n"
+ "IOPS 0.008455 \n",
+ "Stock 0.191968 \n",
+ "TAO 0.255172 \n",
+ "TODS 0.166667 \n",
+ "UCR 0.002503 \n",
+ "WSD 0.166667 \n",
+ "YAHOO 0.030575 \n"
]
}
],
@@ -5687,7 +5700,7 @@
},
{
"cell_type": "code",
- "execution_count": 47,
+ "execution_count": 188,
"metadata": {},
"outputs": [
{
@@ -5695,8 +5708,8 @@
"output_type": "stream",
"text": [
"Anzahl an Datensätzen mit Sequenzanomalien: 158\n",
- "Durchschnittle Gesamt-Performanz des Modells: LOF\n",
- "Recall: 0.042, Precision: 0.364, F1: 0.244, Auc-Roc: 0.567, Auc-PR: 0.150, Vus-PR: 0.158\n"
+ "Durchschnittle Gesamt-Performanz des Modells: Sub-LOF\n",
+ "Recall: 0.261, Precision: 0.397, F1: 0.418, Auc-Roc: 0.726, Auc-PR: 0.330, Vus-PR: 0.393\n"
]
}
],
@@ -5718,81 +5731,81 @@
},
{
"cell_type": "code",
- "execution_count": 48,
+ "execution_count": 189,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- " duration AUC-PR AUC-ROC VUS-PR VUS-ROC Standard-F1 \\\n",
- "group \n",
- "CATSv2 47.136594 0.071542 0.508872 0.063826 0.532996 0.094029 \n",
- "Daphnet 5.897125 0.129509 0.570455 0.134804 0.584871 0.290327 \n",
- "Exathlon 7.824180 0.245106 0.571639 0.240338 0.569108 0.388745 \n",
- "IOPS 38.714642 0.272670 0.793815 0.302989 0.914685 0.418456 \n",
- "LTDB 48.170647 0.203241 0.508966 0.256447 0.535053 0.312078 \n",
- "MGAB 17.135755 0.002209 0.507583 0.004639 0.698543 0.009506 \n",
- "MITDB 187.733897 0.051628 0.508271 0.053749 0.503163 0.099617 \n",
- "MSL 1.721518 0.277979 0.648091 0.327778 0.741380 0.310111 \n",
- "NAB 1.654759 0.154619 0.532240 0.183564 0.583195 0.207639 \n",
- "NEK 0.763594 0.356301 0.681831 0.392335 0.754701 0.448092 \n",
- "OPPORTUNITY 2.579214 0.144952 0.636888 0.152842 0.660690 0.304383 \n",
- "Power 5.743324 0.086245 0.495163 0.090503 0.510731 0.162795 \n",
- "SED 7.071819 0.082198 0.548027 0.111105 0.711726 0.142807 \n",
- "SMAP 1.487841 0.060424 0.516746 0.046142 0.508690 0.073628 \n",
- "SMD 3.725909 0.163313 0.612423 0.137760 0.683553 0.304686 \n",
- "SVDB 36.562070 0.046729 0.511956 0.052218 0.523136 0.088391 \n",
- "SWaT 95.530155 0.120683 0.500025 0.121168 0.500155 0.215281 \n",
- "TODS 4.276212 0.081599 0.519636 0.198760 0.741196 0.147106 \n",
- "WSD 2.849983 0.094898 0.591429 0.073377 0.757073 0.175465 \n",
- "YAHOO 0.650215 0.316546 0.645756 0.304093 0.682903 0.451815 \n",
+ " duration AUC-PR AUC-ROC VUS-PR VUS-ROC Standard-F1 \\\n",
+ "group \n",
+ "CATSv2 298.530087 0.511976 0.740398 0.393045 0.760152 0.575803 \n",
+ "Daphnet 6.632036 0.252282 0.905126 0.253956 0.899824 0.406682 \n",
+ "Exathlon 9.833754 0.257618 0.647576 0.262478 0.653360 0.371983 \n",
+ "IOPS 104.031703 0.157124 0.953948 0.258387 0.945881 0.220766 \n",
+ "LTDB 72.072497 0.333160 0.627012 0.409530 0.712029 0.398966 \n",
+ "MGAB 14.901103 0.567335 0.987331 0.634748 0.995269 0.671333 \n",
+ "MITDB 1327.810889 0.385195 0.760688 0.367125 0.827341 0.431379 \n",
+ "MSL 1.726543 0.368527 0.849005 0.487796 0.891995 0.522580 \n",
+ "NAB 1.640911 0.457316 0.746045 0.511944 0.775067 0.488274 \n",
+ "NEK 0.715299 0.433487 0.762823 0.597690 0.848369 0.528069 \n",
+ "OPPORTUNITY 2.691558 0.154555 0.484578 0.139082 0.505887 0.220768 \n",
+ "Power 7.826579 0.175035 0.552633 0.160858 0.573030 0.211897 \n",
+ "SED 7.801529 0.109660 0.605685 0.253420 0.793686 0.216518 \n",
+ "SMAP 1.277826 0.488277 0.860380 0.599966 0.869912 0.782205 \n",
+ "SMD 4.403478 0.339639 0.770853 0.457631 0.798094 0.444277 \n",
+ "SVDB 90.312594 0.329395 0.705861 0.359030 0.764855 0.403135 \n",
+ "SWaT 183.587712 0.113563 0.375616 0.113915 0.377762 0.220540 \n",
+ "TODS 3.880994 0.240756 0.780922 0.600606 0.914545 0.405820 \n",
+ "WSD 3.245855 0.452830 0.945897 0.608260 0.966831 0.509535 \n",
+ "YAHOO 0.599573 0.242005 0.467560 0.188491 0.459251 0.324732 \n",
"\n",
" PA-F1 Event-based-F1 R-based-F1 Affiliation-F Recall \\\n",
"group \n",
- "CATSv2 0.960104 0.478827 0.188141 0.727454 0.010473 \n",
- "Daphnet 0.980234 0.468354 0.394045 0.798326 0.032090 \n",
- "Exathlon 0.840527 0.678066 0.378081 0.857433 0.027732 \n",
- "IOPS 0.529163 0.583877 0.369894 0.839335 0.238224 \n",
- "LTDB 0.570894 0.420305 0.178030 0.740034 0.004915 \n",
- "MGAB 0.142064 0.020381 0.015286 0.680741 0.023254 \n",
- "MITDB 0.204093 0.103453 0.157732 0.698034 0.000314 \n",
- "MSL 0.960114 0.650977 0.322653 0.772208 0.057901 \n",
- "NAB 0.951826 0.774210 0.310553 0.872314 0.038811 \n",
- "NEK 0.778115 0.704080 0.405725 0.863476 0.146528 \n",
- "OPPORTUNITY 0.621096 0.387623 0.197389 0.780314 0.029576 \n",
- "Power 0.959846 0.171831 0.122386 0.700485 0.009333 \n",
- "SED 0.272876 0.272876 0.074110 0.669564 0.006529 \n",
- "SMAP 0.998141 0.968750 0.363714 0.937230 0.033420 \n",
- "SMD 0.760827 0.469390 0.237546 0.777315 0.080794 \n",
- "SVDB 0.649523 0.274446 0.163110 0.713827 0.007323 \n",
- "SWaT 0.849009 0.177778 0.042904 0.297959 0.000158 \n",
- "TODS 0.677663 0.192700 0.222062 0.695817 0.020832 \n",
- "WSD 0.854583 0.824594 0.357127 0.909645 0.077242 \n",
- "YAHOO 0.973041 0.704260 0.372725 0.801980 0.161590 \n",
+ "CATSv2 0.674950 0.575705 0.232829 0.751034 0.310946 \n",
+ "Daphnet 0.666667 0.420230 0.322369 0.830045 0.117953 \n",
+ "Exathlon 0.800635 0.526162 0.317170 0.804928 0.041724 \n",
+ "IOPS 0.393792 0.277938 0.292347 0.801305 0.221409 \n",
+ "LTDB 0.678791 0.522393 0.319594 0.789237 0.065606 \n",
+ "MGAB 0.712791 0.688846 0.689193 0.960863 0.775952 \n",
+ "MITDB 0.823174 0.687269 0.361808 0.907308 0.267250 \n",
+ "MSL 0.855192 0.577240 0.438985 0.862120 0.034389 \n",
+ "NAB 0.937512 0.845035 0.528333 0.907974 0.094061 \n",
+ "NEK 0.834592 0.765443 0.642710 0.927434 0.192977 \n",
+ "OPPORTUNITY 0.905013 0.790889 0.297577 0.904926 0.131947 \n",
+ "Power 0.913381 0.519774 0.290669 0.782209 0.096000 \n",
+ "SED 0.307548 0.219303 0.070964 0.835491 0.082465 \n",
+ "SMAP 0.949404 0.594994 0.695806 0.928424 0.474002 \n",
+ "SMD 0.706484 0.520657 0.432145 0.882673 0.476923 \n",
+ "SVDB 0.805395 0.680477 0.362640 0.909054 0.289940 \n",
+ "SWaT 0.963075 0.295203 0.095314 0.705366 0.009042 \n",
+ "TODS 0.565282 0.389080 0.344613 0.861731 0.075780 \n",
+ "WSD 0.639516 0.586780 0.547176 0.979343 0.786214 \n",
+ "YAHOO 0.651351 0.455338 0.304982 0.813197 0.133058 \n",
"\n",
" Precision \n",
"group \n",
- "CATSv2 0.895954 \n",
- "Daphnet 0.305785 \n",
- "Exathlon 0.512979 \n",
- "IOPS 0.411365 \n",
- "LTDB 0.265047 \n",
- "MGAB 0.003402 \n",
- "MITDB 0.112437 \n",
- "MSL 0.580518 \n",
- "NAB 0.479673 \n",
- "NEK 0.591503 \n",
- "OPPORTUNITY 0.194188 \n",
- "Power 0.061674 \n",
- "SED 1.000000 \n",
- "SMAP 0.941176 \n",
- "SMD 0.402094 \n",
- "SVDB 0.253079 \n",
- "SWaT 0.242424 \n",
- "TODS 0.057994 \n",
- "WSD 0.359589 \n",
- "YAHOO 0.654752 \n"
+ "CATSv2 0.952401 \n",
+ "Daphnet 0.407186 \n",
+ "Exathlon 0.268818 \n",
+ "IOPS 0.129630 \n",
+ "LTDB 0.528795 \n",
+ "MGAB 0.555421 \n",
+ "MITDB 0.506898 \n",
+ "MSL 0.328403 \n",
+ "NAB 0.593864 \n",
+ "NEK 0.560389 \n",
+ "OPPORTUNITY 0.355430 \n",
+ "Power 0.362720 \n",
+ "SED 0.173993 \n",
+ "SMAP 0.478988 \n",
+ "SMD 0.361177 \n",
+ "SVDB 0.529653 \n",
+ "SWaT 0.055148 \n",
+ "TODS 0.220881 \n",
+ "WSD 0.272025 \n",
+ "YAHOO 0.462963 \n"
]
}
],
@@ -5811,7 +5824,7 @@
},
{
"cell_type": "code",
- "execution_count": 49,
+ "execution_count": 190,
"metadata": {},
"outputs": [
{
@@ -5855,210 +5868,210 @@
" <tbody>\n",
" <tr>\n",
" <th>CATSv2</th>\n",
- " <td>0.071542</td>\n",
- " <td>0.508872</td>\n",
- " <td>0.063826</td>\n",
- " <td>0.094029</td>\n",
- " <td>0.010473</td>\n",
- " <td>0.895954</td>\n",
+ " <td>0.511976</td>\n",
+ " <td>0.740398</td>\n",
+ " <td>0.393045</td>\n",
+ " <td>0.575803</td>\n",
+ " <td>0.310946</td>\n",
+ " <td>0.952401</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Daphnet</th>\n",
- " <td>0.129509</td>\n",
- " <td>0.570455</td>\n",
- " <td>0.134804</td>\n",
- " <td>0.290327</td>\n",
- " <td>0.032090</td>\n",
- " <td>0.305785</td>\n",
+ " <td>0.252282</td>\n",
+ " <td>0.905126</td>\n",
+ " <td>0.253956</td>\n",
+ " <td>0.406682</td>\n",
+ " <td>0.117953</td>\n",
+ " <td>0.407186</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Exathlon</th>\n",
- " <td>0.245106</td>\n",
- " <td>0.571639</td>\n",
- " <td>0.240338</td>\n",
- " <td>0.388745</td>\n",
- " <td>0.027732</td>\n",
- " <td>0.512979</td>\n",
+ " <td>0.257618</td>\n",
+ " <td>0.647576</td>\n",
+ " <td>0.262478</td>\n",
+ " <td>0.371983</td>\n",
+ " <td>0.041724</td>\n",
+ " <td>0.268818</td>\n",
" </tr>\n",
" <tr>\n",
" <th>IOPS</th>\n",
- " <td>0.116787</td>\n",
- " <td>0.629300</td>\n",
- " <td>0.123657</td>\n",
- " <td>0.241223</td>\n",
- " <td>0.092212</td>\n",
- " <td>0.190090</td>\n",
+ " <td>0.263492</td>\n",
+ " <td>0.852975</td>\n",
+ " <td>0.380817</td>\n",
+ " <td>0.350879</td>\n",
+ " <td>0.356618</td>\n",
+ " <td>0.232859</td>\n",
" </tr>\n",
" <tr>\n",
" <th>LTDB</th>\n",
- " <td>0.203241</td>\n",
- " <td>0.508966</td>\n",
- " <td>0.256447</td>\n",
- " <td>0.312078</td>\n",
- " <td>0.004915</td>\n",
- " <td>0.265047</td>\n",
+ " <td>0.333160</td>\n",
+ " <td>0.627012</td>\n",
+ " <td>0.409530</td>\n",
+ " <td>0.398966</td>\n",
+ " <td>0.065606</td>\n",
+ " <td>0.528795</td>\n",
" </tr>\n",
" <tr>\n",
" <th>MGAB</th>\n",
- " <td>0.002209</td>\n",
- " <td>0.507583</td>\n",
- " <td>0.004639</td>\n",
- " <td>0.009506</td>\n",
- " <td>0.023254</td>\n",
- " <td>0.003402</td>\n",
+ " <td>0.567335</td>\n",
+ " <td>0.987331</td>\n",
+ " <td>0.634748</td>\n",
+ " <td>0.671333</td>\n",
+ " <td>0.775952</td>\n",
+ " <td>0.555421</td>\n",
" </tr>\n",
" <tr>\n",
" <th>MITDB</th>\n",
- " <td>0.051628</td>\n",
- " <td>0.508271</td>\n",
- " <td>0.053749</td>\n",
- " <td>0.099617</td>\n",
- " <td>0.000314</td>\n",
- " <td>0.112437</td>\n",
+ " <td>0.385195</td>\n",
+ " <td>0.760688</td>\n",
+ " <td>0.367125</td>\n",
+ " <td>0.431379</td>\n",
+ " <td>0.267250</td>\n",
+ " <td>0.506898</td>\n",
" </tr>\n",
" <tr>\n",
" <th>MSL</th>\n",
- " <td>0.151228</td>\n",
- " <td>0.559967</td>\n",
- " <td>0.186700</td>\n",
- " <td>0.202279</td>\n",
- " <td>0.033586</td>\n",
- " <td>0.644011</td>\n",
+ " <td>0.442670</td>\n",
+ " <td>0.879267</td>\n",
+ " <td>0.544711</td>\n",
+ " <td>0.555176</td>\n",
+ " <td>0.289677</td>\n",
+ " <td>0.468071</td>\n",
" </tr>\n",
" <tr>\n",
" <th>NAB</th>\n",
- " <td>0.144844</td>\n",
- " <td>0.524467</td>\n",
- " <td>0.165966</td>\n",
- " <td>0.205497</td>\n",
- " <td>0.026457</td>\n",
- " <td>0.456076</td>\n",
+ " <td>0.495381</td>\n",
+ " <td>0.730109</td>\n",
+ " <td>0.532450</td>\n",
+ " <td>0.544592</td>\n",
+ " <td>0.148962</td>\n",
+ " <td>0.637919</td>\n",
" </tr>\n",
" <tr>\n",
" <th>NEK</th>\n",
- " <td>0.363561</td>\n",
- " <td>0.668191</td>\n",
- " <td>0.395130</td>\n",
- " <td>0.427307</td>\n",
- " <td>0.168942</td>\n",
- " <td>0.739188</td>\n",
+ " <td>0.554506</td>\n",
+ " <td>0.863816</td>\n",
+ " <td>0.687020</td>\n",
+ " <td>0.655181</td>\n",
+ " <td>0.246789</td>\n",
+ " <td>0.611677</td>\n",
" </tr>\n",
" <tr>\n",
" <th>OPPORTUNITY</th>\n",
- " <td>0.153396</td>\n",
- " <td>0.612566</td>\n",
- " <td>0.159200</td>\n",
- " <td>0.266409</td>\n",
- " <td>0.029277</td>\n",
- " <td>0.293842</td>\n",
+ " <td>0.158653</td>\n",
+ " <td>0.437972</td>\n",
+ " <td>0.149548</td>\n",
+ " <td>0.230552</td>\n",
+ " <td>0.123624</td>\n",
+ " <td>0.407288</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Power</th>\n",
- " <td>0.086245</td>\n",
- " <td>0.495163</td>\n",
- " <td>0.090503</td>\n",
- " <td>0.162795</td>\n",
- " <td>0.009333</td>\n",
- " <td>0.061674</td>\n",
+ " <td>0.175035</td>\n",
+ " <td>0.552633</td>\n",
+ " <td>0.160858</td>\n",
+ " <td>0.211897</td>\n",
+ " <td>0.096000</td>\n",
+ " <td>0.362720</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SED</th>\n",
- " <td>0.082198</td>\n",
- " <td>0.548027</td>\n",
- " <td>0.111105</td>\n",
- " <td>0.142807</td>\n",
- " <td>0.006529</td>\n",
- " <td>1.000000</td>\n",
+ " <td>0.109660</td>\n",
+ " <td>0.605685</td>\n",
+ " <td>0.253420</td>\n",
+ " <td>0.216518</td>\n",
+ " <td>0.082465</td>\n",
+ " <td>0.173993</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SMAP</th>\n",
- " <td>0.180797</td>\n",
- " <td>0.581760</td>\n",
- " <td>0.172499</td>\n",
- " <td>0.231062</td>\n",
- " <td>0.135259</td>\n",
- " <td>0.492777</td>\n",
+ " <td>0.510341</td>\n",
+ " <td>0.828578</td>\n",
+ " <td>0.597854</td>\n",
+ " <td>0.595748</td>\n",
+ " <td>0.524001</td>\n",
+ " <td>0.511394</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SMD</th>\n",
- " <td>0.182353</td>\n",
- " <td>0.632759</td>\n",
- " <td>0.134985</td>\n",
- " <td>0.325650</td>\n",
- " <td>0.109229</td>\n",
- " <td>0.454227</td>\n",
+ " <td>0.486307</td>\n",
+ " <td>0.857014</td>\n",
+ " <td>0.544696</td>\n",
+ " <td>0.565768</td>\n",
+ " <td>0.569888</td>\n",
+ " <td>0.423607</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SVDB</th>\n",
- " <td>0.044940</td>\n",
- " <td>0.512603</td>\n",
- " <td>0.050189</td>\n",
- " <td>0.087034</td>\n",
- " <td>0.006957</td>\n",
- " <td>0.240425</td>\n",
+ " <td>0.356140</td>\n",
+ " <td>0.720499</td>\n",
+ " <td>0.383000</td>\n",
+ " <td>0.422369</td>\n",
+ " <td>0.320710</td>\n",
+ " <td>0.529825</td>\n",
" </tr>\n",
" <tr>\n",
" <th>SWaT</th>\n",
- " <td>0.120683</td>\n",
- " <td>0.500025</td>\n",
- " <td>0.121168</td>\n",
- " <td>0.215281</td>\n",
- " <td>0.000158</td>\n",
- " <td>0.242424</td>\n",
+ " <td>0.113563</td>\n",
+ " <td>0.375616</td>\n",
+ " <td>0.113915</td>\n",
+ " <td>0.220540</td>\n",
+ " <td>0.009042</td>\n",
+ " <td>0.055148</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Stock</th>\n",
- " <td>0.112061</td>\n",
- " <td>0.530383</td>\n",
- " <td>0.710487</td>\n",
- " <td>0.304437</td>\n",
- " <td>0.000000</td>\n",
- " <td>0.000000</td>\n",
+ " <td>0.115033</td>\n",
+ " <td>0.600040</td>\n",
+ " <td>0.747567</td>\n",
+ " <td>0.190880</td>\n",
+ " <td>0.004799</td>\n",
+ " <td>0.191968</td>\n",
" </tr>\n",
" <tr>\n",
" <th>TAO</th>\n",
- " <td>0.167995</td>\n",
- " <td>0.449091</td>\n",
- " <td>0.710584</td>\n",
- " <td>0.230177</td>\n",
- " <td>0.022038</td>\n",
- " <td>0.666667</td>\n",
+ " <td>0.139803</td>\n",
+ " <td>0.612240</td>\n",
+ " <td>0.807694</td>\n",
+ " <td>0.223327</td>\n",
+ " <td>0.017645</td>\n",
+ " <td>0.224967</td>\n",
" </tr>\n",
" <tr>\n",
" <th>TODS</th>\n",
- " <td>0.100820</td>\n",
- " <td>0.536789</td>\n",
- " <td>0.485079</td>\n",
- " <td>0.168044</td>\n",
- " <td>0.027175</td>\n",
- " <td>0.141732</td>\n",
+ " <td>0.166507</td>\n",
+ " <td>0.676933</td>\n",
+ " <td>0.691125</td>\n",
+ " <td>0.270928</td>\n",
+ " <td>0.058744</td>\n",
+ " <td>0.205223</td>\n",
" </tr>\n",
" <tr>\n",
" <th>UCR</th>\n",
- " <td>0.048985</td>\n",
- " <td>0.606013</td>\n",
- " <td>0.051489</td>\n",
- " <td>0.092895</td>\n",
- " <td>0.142430</td>\n",
- " <td>0.071834</td>\n",
+ " <td>0.495182</td>\n",
+ " <td>0.917224</td>\n",
+ " <td>0.514326</td>\n",
+ " <td>0.551956</td>\n",
+ " <td>0.761255</td>\n",
+ " <td>0.238402</td>\n",
" </tr>\n",
" <tr>\n",
" <th>WSD</th>\n",
- " <td>0.141918</td>\n",
- " <td>0.638387</td>\n",
- " <td>0.102346</td>\n",
- " <td>0.225878</td>\n",
- " <td>0.153504</td>\n",
- " <td>0.331186</td>\n",
+ " <td>0.539254</td>\n",
+ " <td>0.959885</td>\n",
+ " <td>0.551041</td>\n",
+ " <td>0.594305</td>\n",
+ " <td>0.798756</td>\n",
+ " <td>0.265358</td>\n",
" </tr>\n",
" <tr>\n",
" <th>YAHOO</th>\n",
- " <td>0.409909</td>\n",
- " <td>0.828505</td>\n",
- " <td>0.381508</td>\n",
- " <td>0.443120</td>\n",
- " <td>0.448921</td>\n",
- " <td>0.295807</td>\n",
+ " <td>0.150503</td>\n",
+ " <td>0.916171</td>\n",
+ " <td>0.451001</td>\n",
+ " <td>0.237975</td>\n",
+ " <td>0.564290</td>\n",
+ " <td>0.068880</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
@@ -6067,32 +6080,32 @@
"text/plain": [
" AUC-PR AUC-ROC VUS-PR Standard-F1 Recall Precision\n",
"group \n",
- "CATSv2 0.071542 0.508872 0.063826 0.094029 0.010473 0.895954\n",
- "Daphnet 0.129509 0.570455 0.134804 0.290327 0.032090 0.305785\n",
- "Exathlon 0.245106 0.571639 0.240338 0.388745 0.027732 0.512979\n",
- "IOPS 0.116787 0.629300 0.123657 0.241223 0.092212 0.190090\n",
- "LTDB 0.203241 0.508966 0.256447 0.312078 0.004915 0.265047\n",
- "MGAB 0.002209 0.507583 0.004639 0.009506 0.023254 0.003402\n",
- "MITDB 0.051628 0.508271 0.053749 0.099617 0.000314 0.112437\n",
- "MSL 0.151228 0.559967 0.186700 0.202279 0.033586 0.644011\n",
- "NAB 0.144844 0.524467 0.165966 0.205497 0.026457 0.456076\n",
- "NEK 0.363561 0.668191 0.395130 0.427307 0.168942 0.739188\n",
- "OPPORTUNITY 0.153396 0.612566 0.159200 0.266409 0.029277 0.293842\n",
- "Power 0.086245 0.495163 0.090503 0.162795 0.009333 0.061674\n",
- "SED 0.082198 0.548027 0.111105 0.142807 0.006529 1.000000\n",
- "SMAP 0.180797 0.581760 0.172499 0.231062 0.135259 0.492777\n",
- "SMD 0.182353 0.632759 0.134985 0.325650 0.109229 0.454227\n",
- "SVDB 0.044940 0.512603 0.050189 0.087034 0.006957 0.240425\n",
- "SWaT 0.120683 0.500025 0.121168 0.215281 0.000158 0.242424\n",
- "Stock 0.112061 0.530383 0.710487 0.304437 0.000000 0.000000\n",
- "TAO 0.167995 0.449091 0.710584 0.230177 0.022038 0.666667\n",
- "TODS 0.100820 0.536789 0.485079 0.168044 0.027175 0.141732\n",
- "UCR 0.048985 0.606013 0.051489 0.092895 0.142430 0.071834\n",
- "WSD 0.141918 0.638387 0.102346 0.225878 0.153504 0.331186\n",
- "YAHOO 0.409909 0.828505 0.381508 0.443120 0.448921 0.295807"
+ "CATSv2 0.511976 0.740398 0.393045 0.575803 0.310946 0.952401\n",
+ "Daphnet 0.252282 0.905126 0.253956 0.406682 0.117953 0.407186\n",
+ "Exathlon 0.257618 0.647576 0.262478 0.371983 0.041724 0.268818\n",
+ "IOPS 0.263492 0.852975 0.380817 0.350879 0.356618 0.232859\n",
+ "LTDB 0.333160 0.627012 0.409530 0.398966 0.065606 0.528795\n",
+ "MGAB 0.567335 0.987331 0.634748 0.671333 0.775952 0.555421\n",
+ "MITDB 0.385195 0.760688 0.367125 0.431379 0.267250 0.506898\n",
+ "MSL 0.442670 0.879267 0.544711 0.555176 0.289677 0.468071\n",
+ "NAB 0.495381 0.730109 0.532450 0.544592 0.148962 0.637919\n",
+ "NEK 0.554506 0.863816 0.687020 0.655181 0.246789 0.611677\n",
+ "OPPORTUNITY 0.158653 0.437972 0.149548 0.230552 0.123624 0.407288\n",
+ "Power 0.175035 0.552633 0.160858 0.211897 0.096000 0.362720\n",
+ "SED 0.109660 0.605685 0.253420 0.216518 0.082465 0.173993\n",
+ "SMAP 0.510341 0.828578 0.597854 0.595748 0.524001 0.511394\n",
+ "SMD 0.486307 0.857014 0.544696 0.565768 0.569888 0.423607\n",
+ "SVDB 0.356140 0.720499 0.383000 0.422369 0.320710 0.529825\n",
+ "SWaT 0.113563 0.375616 0.113915 0.220540 0.009042 0.055148\n",
+ "Stock 0.115033 0.600040 0.747567 0.190880 0.004799 0.191968\n",
+ "TAO 0.139803 0.612240 0.807694 0.223327 0.017645 0.224967\n",
+ "TODS 0.166507 0.676933 0.691125 0.270928 0.058744 0.205223\n",
+ "UCR 0.495182 0.917224 0.514326 0.551956 0.761255 0.238402\n",
+ "WSD 0.539254 0.959885 0.551041 0.594305 0.798756 0.265358\n",
+ "YAHOO 0.150503 0.916171 0.451001 0.237975 0.564290 0.068880"
]
},
- "execution_count": 49,
+ "execution_count": 190,
"metadata": {},
"output_type": "execute_result"
}
@@ -6105,40 +6118,40 @@
},
{
"cell_type": "code",
- "execution_count": 50,
+ "execution_count": 191,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"group\n",
- "MGAB 0.002209\n",
- "SVDB 0.044940\n",
- "UCR 0.048985\n",
- "MITDB 0.051628\n",
- "CATSv2 0.071542\n",
- "SED 0.082198\n",
- "Power 0.086245\n",
- "TODS 0.100820\n",
- "Stock 0.112061\n",
- "IOPS 0.116787\n",
- "SWaT 0.120683\n",
- "Daphnet 0.129509\n",
- "WSD 0.141918\n",
- "NAB 0.144844\n",
- "MSL 0.151228\n",
- "OPPORTUNITY 0.153396\n",
- "TAO 0.167995\n",
- "SMAP 0.180797\n",
- "SMD 0.182353\n",
- "LTDB 0.203241\n",
- "Exathlon 0.245106\n",
- "NEK 0.363561\n",
- "YAHOO 0.409909\n",
+ "SED 0.109660\n",
+ "SWaT 0.113563\n",
+ "Stock 0.115033\n",
+ "TAO 0.139803\n",
+ "YAHOO 0.150503\n",
+ "OPPORTUNITY 0.158653\n",
+ "TODS 0.166507\n",
+ "Power 0.175035\n",
+ "Daphnet 0.252282\n",
+ "Exathlon 0.257618\n",
+ "IOPS 0.263492\n",
+ "LTDB 0.333160\n",
+ "SVDB 0.356140\n",
+ "MITDB 0.385195\n",
+ "MSL 0.442670\n",
+ "SMD 0.486307\n",
+ "UCR 0.495182\n",
+ "NAB 0.495381\n",
+ "SMAP 0.510341\n",
+ "CATSv2 0.511976\n",
+ "WSD 0.539254\n",
+ "NEK 0.554506\n",
+ "MGAB 0.567335\n",
"Name: AUC-PR, dtype: float64"
]
},
- "execution_count": 50,
+ "execution_count": 191,
"metadata": {},
"output_type": "execute_result"
}
@@ -6150,40 +6163,40 @@
},
{
"cell_type": "code",
- "execution_count": 51,
+ "execution_count": 192,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"group\n",
- "MGAB 0.004639\n",
- "SVDB 0.050189\n",
- "UCR 0.051489\n",
- "MITDB 0.053749\n",
- "CATSv2 0.063826\n",
- "Power 0.090503\n",
- "WSD 0.102346\n",
- "SED 0.111105\n",
- "SWaT 0.121168\n",
- "IOPS 0.123657\n",
- "Daphnet 0.134804\n",
- "SMD 0.134985\n",
- "OPPORTUNITY 0.159200\n",
- "NAB 0.165966\n",
- "SMAP 0.172499\n",
- "MSL 0.186700\n",
- "Exathlon 0.240338\n",
- "LTDB 0.256447\n",
- "YAHOO 0.381508\n",
- "NEK 0.395130\n",
- "TODS 0.485079\n",
- "Stock 0.710487\n",
- "TAO 0.710584\n",
+ "SWaT 0.113915\n",
+ "OPPORTUNITY 0.149548\n",
+ "Power 0.160858\n",
+ "SED 0.253420\n",
+ "Daphnet 0.253956\n",
+ "Exathlon 0.262478\n",
+ "MITDB 0.367125\n",
+ "IOPS 0.380817\n",
+ "SVDB 0.383000\n",
+ "CATSv2 0.393045\n",
+ "LTDB 0.409530\n",
+ "YAHOO 0.451001\n",
+ "UCR 0.514326\n",
+ "NAB 0.532450\n",
+ "SMD 0.544696\n",
+ "MSL 0.544711\n",
+ "WSD 0.551041\n",
+ "SMAP 0.597854\n",
+ "MGAB 0.634748\n",
+ "NEK 0.687020\n",
+ "TODS 0.691125\n",
+ "Stock 0.747567\n",
+ "TAO 0.807694\n",
"Name: VUS-PR, dtype: float64"
]
},
- "execution_count": 51,
+ "execution_count": 192,
"metadata": {},
"output_type": "execute_result"
}