# count = 0
# for i in range(y22.shape[0]):
# if y22[i] == y_test22[i]:
# count+=1
#
# print('Accuracy for model 2 : ' + str((count / y22.shape[0]) * 100))
#
# X_train2,X_test2,y_train2,y_test2 = train_test_split(feature_all, y, test_size = 0.3, random_state=20)
########################### MODEL 3 ###########################
model3 = XGBClassifier()
#TODO fit generator
model3.fit_generator(train_generator,
steps_per_epoch=15,
epochs=50,
validation_data=validation_generator,
validation_steps=5)
model3.evals_result()
#TODO
score = cross_val_score(model3, X_train2, y_train2, cv=5)
#TODO predict generator
y_pred3 = model3.predict_generator(validation_generator, steps=5)
count = 0
for i in range(y_pred3.shape[0]):
# if y_pred3[i] == y_test2[i]:
# count+=1
#TODO compare with actual label
