# fit the model
model.fit(X_train, y_train)
# save the model
import pickle
pickle.dump(model, open("model.pkl", "wb"))
# load the model
model = pickle.load(open("model.pkl", "rb"))
# use model to predict
y_pred = model.predict(X_input)
model.fit(X_train, Y_train)
# save the model to disk
filename = 'finalized_model.sav'
pickle.dump(model, open(filename, 'wb'))
# load the model from disk
loaded_model = pickle.load(open(filename, 'rb'))
result = loaded_model.score(X_test, Y_test)