numpy.linalg.norm是否可以将sklearn.preprocessing.normalize（X，norm ='l1'，）替换为矩阵的L1-norm？

Question

I used sklearn.preprocessing.normalize before but I wonder there are other ways by Numpy (or something else) for L1-norm of matrix? Can we use numpy.linalg.norm(x, ord=None, axis=None, keepdims=False) instead of sklearn one?

According to the document , linalg.norm params seem not possible for matrix nor L1

x : array_like Input array. If axis is None, x must be 1-D or 2-D.
ord : {non-zero int, inf, -inf, ‘fro’, ‘nuc’}, optional

Answer 1

Yes. numpy.linalg.norm is for Matrix or vector norm.

It depends on which kind of L1 matrix norm you want. You can specify it with argument ord . ( Doc )

numpy.linalg.norm(x, ord=None, axis=None, keepdims=False)

Matrix norms induced by vector norms, ord=inf

"Entrywise" matrix norms, ord=0

Schatten norms, ord=nuc