model pickle file create
import pickle
# 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)save machine learning model python
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)python pickle example
import pickle
favorite_color = { "lion": "yellow", "kitty": "red" }
with open( "save.p", "wb" ) as f:
pickle.dump( favorite_color, f)
with open( "save.p", "rb" ) as f:
favorite_color = pickle.load(f)Copyright © 2021 Codeinu
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