LinearClassification.py 文件源码

def transform(self, X, y):
        """transform function"""
        XMat = np.array(X)
        yMat = np.array(y)

        if XMat.shape[0] != yMat.shape[0]:
            yMat = yMat.T
        assert XMat.shape[0] == yMat.shape[0]

        XMat -= XMat.mean(axis=0)
        Sw, Sb = calc_Sw_Sb(XMat, yMat)

        if self.method == 'svd':
            U, S, V = np.linalg.svd(Sw)
            S = np.diag(S)
            Sw_inversed = V * np.linalg.pinv(S) * U.T
            A = Sw_inversed * Sb
        elif self.method == 'auto':
            A = np.linalg.pinv(Sw) * Sb

        eigval, eigvec = np.linalg.eig(A)
        eigval = eigval[0:self.n_components]
        eigvec = eigvec[:, 0:self.n_components]
        X_transformed = np.dot(XMat, eigvec)
        self.W = eigvec

        return X_transformed