def __init__(self, neg_label=0, pos_label=1, sparse_output=False):
        if neg_label >= pos_label:
            raise ValueError("neg_label={0} must be strictly less than "
                             "pos_label={1}.".format(neg_label, pos_label))

        if sparse_output and (pos_label == 0 or neg_label != 0):
            raise ValueError("Sparse binarization is only supported with non "
                             "zero pos_label and zero neg_label, got "
                             "pos_label={0} and neg_label={1}"
                             "".format(pos_label, neg_label))

        self.neg_label = neg_label
        self.pos_label = pos_label
        self.sparse_output = sparse_output
dataset/ETHPy150Open scikit-learn/scikit-learn/sklearn/preprocessing/label.py/LabelBinarizer.__init__/original