flask_6.py

# create the object of LinearRegression Model
model_LR = LogisticRegression()

# fit the model with the training data
model_LR.fit(train_idf, train.label)

# predict the label on the traning data
predict_train = model_LR.predict(train_idf)

# predict the model on the test data
predict_test = model_LR.predict(test_idf)

# f1 score on train data
f1_score(y_true= train.label, y_pred= predict_train)
## >> 0.4888178913738019

f1_score(y_true= test.label, y_pred= predict_test)
## >> 0.45751633986928114