scikit-learn的基本用法——模型保存與加載

import pickle
from sklearn.svm import SVC
from sklearn import datasets

# 定義分類器
svm = SVC()

# 加載iris數據集
iris = datasets.load_iris()
# 讀取特徵
X = iris.data
# 讀取分類標籤
y = iris.target

# 訓練模型
svm.fit(X, y)

# 保存成python支持的文件格式pickle, 在當前目錄下可以看到svm.pickle
with open('svm.pickle', 'wb') as fw:
    pickle.dump(svm, fw)

# 加載svm.pickle
with open('svm.pickle', 'rb') as fr:
    new_svm = pickle.load(fr)
    print new_svm.predict(X[0:1])