Re: [scikit-learn] Truncated svd not working for complex matrices

Should we be more explicitly forbidding complex data in most estimators, and perhaps allow it in a few where it is tested (particularly decomposition)? On 11 August 2017 at 01:08, André Melo wrote: > Actually, it makes more sense to change > > B =

Re: [scikit-learn] Truncated svd not working for complex matrices

I have no idea whether the randomized SVD method is supposed to work for complex data or not (from a mathematical point of view). I think that all scikit-learn estimators assume real data (or integer data for class labels) and our input validation utilities will cast numeric values to float64 by

[scikit-learn] Truncated svd not working for complex matrices

Hello all, I'm trying to use the randomized version of scikit-learn's TruncatedSVD (although I'm actually calling the internal function randomized_svd to get the actual u, s, v matrices). While it is working fine for real matrices, for complex matrices I can't get back the original matrix even