模型存储

 

pickle

可以通过使用Python的内置持久化模型（即pickle）将模型保存在scikit中：

from sklearn import svm

from sklearn import datasets

clf = svm.SVC()

iris = datasets.load_iris()

X, y = iris.data, iris.target

clf.fit(X, y)

import pickle

s = pickle.dumps(clf)

clf2 = pickle.loads(s)

clf2.predict(X[0:1])

>>>array([0])

joblib

对于在内部携带大量numpy数组的对象来说，joblib相比pickle效率更高

from sklearn.externals import joblib

joblib.dump(clf, 'filename.pkl')

clf = joblib.load('filename.pkl')