一、模型建立

from sklearn import svm
from sklearn import datasetsclf = svm.SVC()
iris = datasets.load_iris()
X, y = iris.data, iris.target
clf.fit(X, y)

二、保存法1：pickle

保存模型

import pickle
with open('../save/clf.pickle', 'wb') as f:pickle.dump(clf, f)

调用模型

import pickle
with open('../save/clf.pickle', 'rb') as f:clf2 = pickle.load(f)print(clf2.predict(X[0:1]))

三、保存法2：joblib

保存模型

import joblib
joblib.dump(clf, '../save/clf.pkl')

调用模型

clf3 = joblib.load('../save/clf.pkl')
print(clf3.predict(X[0:1]))