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)pickle save
import pickle
a = {'hello': 'world'}
with open('filename.pickle', 'wb') as handle:
pickle.dump(a, handle, protocol=pickle.HIGHEST_PROTOCOL)
with open('filename.pickle', 'rb') as handle:
b = pickle.load(handle)
print a == bsave 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)pickle save
import pickle
pickle.dump( favorite_color, open( "save.p", "wb" ) )
favorite_color = pickle.load( open( "save.p", "rb" ) )save object pickle python
import pickle object = Object() filehandler = open(filename, 'w') pickle.dump(object, filehandler)save object pickle python
import pickle filehandler = open(filename, 'r') object = pickle.load(filehandler)Copyright © 2021 Codeinu
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