model.fit(X_train, Y_train)
# save the model to disk
filename = 'finalized_model.sav'
pickle.dump(model, open(filename, 'wb'))
# some time later...
# load the model from disk
loaded_model = pickle.load(open(filename, 'rb'))
result = loaded_model.score(X_test, Y_test)
print(result)
import pickle # first import library
pickle.dump(model, open("any_model_name.pkl", "wb"))
import pickle
# To save
pickle.dump(model, "model.p")
# To load again
with open('model.p', 'r') as fp:
model = pickle.load(fp)