Nachricht def training_data(classifier, tfidf, df):

def training_data(classifier, tfidf, df): '''Here we split our data set into train and test. We take the data and split the tweets and labels into 2 parts. The bigger part is used for training and the rest is used to testing the data ''' # Split data set: tweet_train, tweet_test, signal_train, signal_test = train_test_split(tfidf, df[8], test_size=0.3, #'Label random_state=42) classify = classifier # Load trainer model. cls = classify.fit(tweet_train, signal_train) # Train data. predict = cls.predict(tweet_test) # Predict data. # Save the model to disk filename = str(classifier).split('(',1)[0] + '.sav' pickle.dump(cls, open(filename, 'wb')) print(filename + ' result:') return classification_report(signal_test, predict) # Give report or evaluation.