>>>>>> 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,   decision_function_shape='ovr', degree=3, gamma='auto', 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[0:1]) array([0]) 
>>> y[0] 0