(y, dims=1)
return y.mapValues(lambda x: np.zeros(dims)), np.zeros(dims)
The initialize value if using softmax cross entropy loss,
            this function mainly uses in secureboost's tree value initialize

        Parameters
        ----------
        y : Table
            The input data's labels

        dims: the nums of different category labels

        Returns
        -------
        y_initialize : table, the value of the table is a 1D numpy ndarray
            with shape equals to dims, which filled with zeros
The initialize value if using softmax cross entropy loss,
            this function mainly uses in secureboost's tree value initialize
The initialize value if using softmax cross entropy loss this function mainly uses in secureboost s tree value initialize
def initialize(y, dims=1):
        """
        The initialize value if using softmax cross entropy loss,
            this function mainly uses in secureboost's tree value initialize

        Parameters
        ----------
        y : Table
            The input data's labels

        dims: the nums of different category labels

        Returns
        -------
        y_initialize : table, the value of the table is a 1D numpy ndarray
            with shape equals to dims, which filled with zeros

        """
        return y.mapValues(lambda x: np.zeros(dims)), np.zeros(dims)
def initialize ( y , dims = 1 ) : return y . mapValues ( lambda x : np . zeros ( dims ) ) , np . zeros ( dims )