from sklearn.externals import joblib
joblib.dump(svc,'project21-carcomforttype.obj')
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model=joblib.load('project21-carcomforttype.obj')
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Final_predictions=model.predict(x_test)
Final_predictions=pd.DataFrame(Final_predictions,columns=['unacc(0),acc(1),good(2),vgood(3)'])
Final_predictions[:5]
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Final_predictions.sample(n=10)
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#Saving final predictions in file.csv format
Final_predictions.to_csv('E:final_predictionscarcomforttype',index=False)
from math import sqrt
>>> from joblib import Parallel, delayed
>>> Parallel(n_jobs=2)(delayed(sqrt)(i ** 2) for i in range(10))
[0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0]
joblib.dump(svc,'project21-carcomforttype.obj')
model=joblib.load('project21-carcomforttype.obj')