def start(self, ds=Config.DATASET_NAME):
self.dataset_name = ds
dataset = DataHandler(dataset_name=ds)
L_X, L_y, U_X, X_test, y_test = dataset.data_split(
label_rate=self.label_rate, test_rate=Config.TEST_RATE)
classifier = Classifier(Config.CLASSIFIER)
t_training = TriTraining(classifier.get_classifier(),
self.is_extract_meta_features,
self.model_type)
if self.is_extract_meta_features:
self.meta_features = MetaFeaturesExtracion()
self.meta_features.dataset_based_mf(dataset, classifier)
t_training.set_meta_features_extractor(self.meta_features)
t_training.fit(dataset)
self.res = t_training.predict(X_test)
self.evaluation = t_training.score(X_test, y_test)
