test_data.py 文件源码

def to_one_hot(y):
    """Transform multi-class labels to binary labels
        The output of to_one_hot is sometimes referred to by some authors as the
        1-of-K coding scheme.
        Parameters
        ----------
        y : numpy array or sparse matrix of shape (n_samples,) or
            (n_samples, n_classes) Target values. The 2-d matrix should only
            contain 0 and 1, represents multilabel classification. Sparse
            matrix can be CSR, CSC, COO, DOK, or LIL.
        Returns
        -------
        Y : numpy array or CSR matrix of shape [n_samples, n_classes]
            Shape will be [n_samples, 1] for binary problems.
        classes_ : class vector extraceted from y.
        """
    lb = LabelBinarizer()
    lb.fit(y)
    Y = lb.transform(y)
    return (Y.base, lb.classes_)