决策树

标签二值化

>>> from sklearn import preprocessing>>> lb = preprocessing.LabelBinarizer()>>> lb.fit([1, 2, 6, 4, 2])LabelBinarizer(neg_label=0, pos_label=1, sparse_output=False)>>> lb.classes_array([1, 2, 4, 6])>>> lb.transform([1, 6])array([[1, 0, 0, 0],       [0, 0, 0, 1]])

>>> lb = preprocessing.LabelBinarizer()>>> lb.fit_transform(['yes', 'no', 'no', 'yes'])array([[1],       [0],       [0],       [1]])