pca.py 文件源码

def fit(self, X):
        n_samples, n_featurs = X.shape
        K = self.kernel.inner(X, X)
        I1N = sp.ones((n_samples, n_samples))
        K_centered = K - sp.dot(I1N, K) - sp.dot(K, I1N) + sp.dot(sp.dot(I1N, K), I1N)

        eigvals, eigvecs = self._eig_decomposition(K_centered)

        self.eigvals = eigvals
        self.eigvecs = eigvecs

        Y = sp.dot(K, eigvecs)

        return Y