[scikit-learn] nmf with multiple cores

I’m running nmf on a machine with 16 cores. Is there an option to run nmf with multithreading? I know numpy does, but all I see is one single process with 100% CPU usage. Thanks, ___ scikit-learn mailing list scikit-learn@python.org https://mail.pyt

[scikit-learn] gradient boosting regression with multiple output variables?

I noticed that the fit method of GBR does not return a [n_samples, n_output] array. Does that mean multiple output variables are not supported? I'm asking because most other regressors do. Thank you, ___ scikit-learn mailing list scikit-learn@python.o

Re: [scikit-learn] joblib deprecation warning

Thank you, On 29/05/2016, 16:58, "scikit-learn on behalf of Alexandre Abadie" wrote: >Hi, > >Thanks for reporting. >This is a known issue from joblib already reported in [1] and fixed by [2]. > >Alex > >[1] https://github.com/joblib/joblib/issues/308 >[2] https://github.com/joblib/joblib/p

[scikit-learn] random forest regression with multiple output variables

When using random forest regressor, the default scoring function is mse. In the case of multiple output, is the mse the sum over all output variables? If so, are the output variables scaled, to make the mse comparable across different variables? Thank you, _

[scikit-learn] joblib deprecation warning

I'm getting the following warning with anaconda anaconda2/lib/python2.7/site-packages/sklearn/externals/joblib/hashing.py:197: DeprecationWarning: Changing the shape of non-C contiguous array by descriptor assignment is deprecated. To maintain the Fortran contiguity of a multidimensional Fortr