sparse_als_soft_impute.py 文件源码

def _svd(self, X, max_rank=None):
        if max_rank:
            # if we have a max rank then perform the faster randomized SVD
            return randomized_svd(
                X,
                max_rank,
                n_iter=self.n_power_iterations)
        else:
            # perform a full rank SVD using ARPACK
            return np.linalg.svd(
                X,
                full_matrices=False,
                compute_uv=True)