sklearn 中模型保存的两种方法

一、sklearn中提供了高效的模型持久化模块joblib，将模型保存至硬盘。

fromsklearn.externalsimportjoblib
#lr是一个LogisticRegression模型
joblib.dump(lr,'lr.model')
lr=joblib.load('lr.model')

链接：https://www.zhihu.com/question/27187105/answer/55895472

二、pickle

>>>fromsklearnimportsvm
>>>fromsklearnimportdatasets
>>>clf=svm.SVC()
>>>iris=datasets.load_iris()
>>>X,y=iris.data,iris.target
>>>clf.fit(X,y)
SVC(C=1.0,cache_size=200,class_weight=None,coef0=0.0,
decision_function_shape=None,degree=3,gamma='auto',kernel='rbf',
max_iter=-1,probability=False,random_state=None,shrinking=True,
tol=0.001,verbose=False)

>>>importpickle
>>>s=pickle.dumps(clf)
>>>clf2=pickle.loads(s)
>>>clf2.predict(X[0:1])
array([0])
>>>y[0]
0

或者：

>>>fromsklearn.externalsimportjoblib
>>>joblib.dump(clf,'filename.pkl')
>>>clf=joblib.load('filename.pkl')

链接：https://www.zhihu.com/question/27187105/answer/97334347