def evaluate(self):
self.Y_predicted = self.model.predict(self.X_test)
self.Y_predicted = np.argmax(self.Y_predicted, axis=1)
self.Y_predicted = [
self.labels_dict_rev[int(i)] for i in list(self.Y_predicted)
]
self.Y_test = np.argmax(self.Y_test, axis=1)
self.Y_test = [self.labels_dict_rev[int(i)] for i in list(self.Y_test)]
self.accuracy, self.precision, self.recall, self.f1score = BasicFunctions.getMetrics(
self.Y_test, self.Y_predicted, self.labels)
def evaluate(self):
self.Y_predicted = self.classifier.predict(self.X_test)
self.accuracy, self.precision, self.recall, self.f1score = BasicFunctions.getMetrics(
self.Y_test, self.Y_predicted, self.labels)