Routines.py 文件源码

def eval_classificationT( self, y, p_y):
        """Calculate the error (100 - accuracy) of the DNN in the case of classification.

        :type y: vector 
        :param y: vector (r,) of labels

        :type p_y: matrix
        :param p_y: matrix of the output of the network. Each raw is a vector of probailities (probablities of the classes)
        """

        y_ = T.argmax(p_y, axis = 1)
        # Accuracy
        error = 1 - T.mean(T.eq(y_, y) * 1.)
        error = error * 100.

        return error