Classifier

[jan-gerling]

SVM classifier (160k, 0.2 positive balance): https://drive.google.com/file/d/1FulPT0ytri2ODRG5Oa54-Ci_NmNagmUw/view?usp=sharing
svm.SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0, decision_function_shape='ovr', degree=3, gamma='scale', kernel='rbf', max_iter=-1, probability=False, random_state=None, shrinking=True, tol=0.001, verbose=False)

-----------------------RESULTS-----------------------
20000
Accuracy: 0.946
Jaccard Index: 0.377
Precision: 0.46747676912080055
Recall: 0.6612740141557129
Average precision: 0.32588023964105517
-----------------------END RESULTS-----------------------

[jan-gerling]

SVM classifier (16k, 0.2 positive balance):

svm.SVC(kernel='rbf', C=1.0, cache_size=500, class_weight=None, coef0=0.0,
                               decision_function_shape='ovr', degree=3, max_iter=-1, probability=False,
                               random_state=None, shrinking=True, tol=0.001, verbose=False)
Best parameter for svm: {'C': 1, 'gamma': 0.01}

-----------------------RESULTS-----------------------
20000svm
Accuracy: 0.9123
Jaccard Index: 0.33
Precision: 0.34657039711191334
Recall: 0.8736097067745198
Average precision: 0.30901726299766746
-----------------------END RESULTS-----------------------

[jan-gerling]

All classifier (svm and random forest with varying configs and training data set sizes):
https://drive.google.com/file/d/1TReBbGlpujMPRR4vK9Ipr3tFp21H4Lsv/view?usp=sharing