将分类器保存到scikit-learn中的磁盘 [英] Save classifier to disk in scikit-learn

问题描述

如何将训练有素的朴素贝叶斯分类器保存到磁盘并用于预测数据?

How do I save a trained Naive Bayes classifier to disk and use it to predict data?

我从scikit-learn网站获得以下示例程序:

I have the following sample program from the scikit-learn website:

from sklearn import datasets
iris = datasets.load_iris()
from sklearn.naive_bayes import GaussianNB
gnb = GaussianNB()
y_pred = gnb.fit(iris.data, iris.target).predict(iris.data)
print "Number of mislabeled points : %d" % (iris.target != y_pred).sum()

推荐答案

分类器只是可以像其他任何东西一样被腌制和转储的对象.继续您的示例:

Classifiers are just objects that can be pickled and dumped like any other. To continue your example:

import cPickle
# save the classifier
with open('my_dumped_classifier.pkl', 'wb') as fid:
    cPickle.dump(gnb, fid)    

# load it again
with open('my_dumped_classifier.pkl', 'rb') as fid:
    gnb_loaded = cPickle.load(fid)

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