nystrom.py 文件源码

def fit(self, graphs, y=None):
        rnd = check_random_state(self.random_state)
        n_samples = len(graphs)

        # get basis vectors
        if self.n_components > n_samples:
            n_components = n_samples
        else:
            n_components = self.n_components
        n_components = min(n_samples, n_components)
        inds = rnd.permutation(n_samples)
        basis_inds = inds[:n_components]
        basis = []
        for ind in basis_inds:
            basis.append(graphs[ind])

        basis_kernel = self.kernel(basis, basis, **self._get_kernel_params())

        # sqrt of kernel matrix on basis vectors
        U, S, V = svd(basis_kernel)
        S = np.maximum(S, 1e-12)
        self.normalization_ = np.dot(U * 1. / np.sqrt(S), V)
        self.components_ = basis
        self.component_indices_ = inds
        return self