def sgd(self, label, result_list):
clf = SGDClassifier()
return execute_decision_function(clf, self.train_test_split, label, result_list, self.image_creator)
def adaboost(self, label, result_list):
clf = AdaBoostClassifier()
return execute_decision_function(clf, self.train_test_split, label, result_list, self.image_creator)
def svm_linearsvc(self, label, result_list):
clf = svm.LinearSVC()
return execute_decision_function(clf, self.train_test_split, label, result_list, self.image_creator)
def logistic_regression(self, label, result_list):
clf = LogisticRegression(max_iter=1000)
return execute_decision_function(clf, self.train_test_split, label, result_list, self.image_creator)
def svm_svc(self, label, result_list):
clf = svm.SVC(kernel='rbf')
return execute_decision_function(clf, self.train_test_split, label, result_list, self.image_creator)
def local_outlier_factor(self, label, result_list):
clf = LocalOutlierFactor(novelty=True)
return execute_decision_function(clf, self.train_test_split, label, result_list, self.image_creator,
unsupervised=True)
def iso_forest(self, label, result_list):
x_train = self.train_test_split['x_train']
clf = ensemble.IsolationForest(max_samples=x_train.shape[0], random_state=None)
return execute_decision_function(clf, self.train_test_split, label, result_list, self.image_creator,
unsupervised=True)
def elliptic_envelope(self, label, result_list):
clf = covariance.EllipticEnvelope(support_fraction=1)
return execute_decision_function(clf, self.train_test_split, label, result_list, self.image_creator,
unsupervised=True)
def svm_oneclass(self, label, result_list):
clf = svm.OneClassSVM()
return execute_decision_function(clf, self.train_test_split, label, result_list, self.image_creator,
unsupervised=True)