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feat(Reporting): added robustness / correlation test (#138)

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* feat(Evaluation): added robustness/correlation test

* feat(Reporting): saving correlations

* fix(Reporting): record correlations properly

* fix(Model): SVC's random seed

* feat(CI): store artifacts
This commit is contained in:
Mark Aron Szulyovszky
2022-01-09 20:00:03 +01:00
committed by GitHub
parent b1c04afb13
commit f5bbc266a4
5 changed files with 39 additions and 8 deletions
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models/model_map.py
+1 -1
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@@ -53,7 +53,7 @@ model_map = {
NB= SKLearnModel(GaussianNB()),
AB= SKLearnModel(AdaBoostClassifier(n_estimators=15)),
RF= SKLearnModel(RandomForestClassifier(n_jobs=-1, max_depth=20, random_state=1)),
SVC = SKLearnModel(SVC(kernel='rbf', C=1e3, probability=True)),
SVC = SKLearnModel(SVC(kernel='rbf', C=1e3, probability=True, random_state=1)),
XGB_two_class= XGBoostModel(XGBClassifier(n_jobs=-1, max_depth = 20, random_state=1, objective='binary:logistic', use_label_encoder= False, eval_metric='mlogloss')),
LGBM = SKLearnModel(LGBMClassifier(n_jobs=-1, max_depth=20, random_state=1)),
StaticMom= StaticMomentumModel(allow_short=True),