擅长:python、mysql、java
<p>从<a href="http://scikit-learn.org/stable/tutorial/basic/tutorial.html" rel="noreferrer">this tutorial</a>的模型持久性部分可以看出:</p>
<p>通过使用Python的内置持久性模型,即<a href="http://docs.python.org/library/pickle.html" rel="noreferrer">pickle</a>,可以在scikit中保存一个模型:</p>
<pre><code>>>> 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)
SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0, degree=3, gamma=0.0,
kernel='rbf', max_iter=-1, probability=False, random_state=None,
shrinking=True, tol=0.001, verbose=False)
>>> import pickle
>>> s = pickle.dumps(clf)
>>> clf2 = pickle.loads(s)
>>> clf2.predict(X[0])
array([0])
>>> y[0]
0
</code></pre>