Re: [scikit-learn] Vote on SLEP009: keyword only arguments

I vote +1 Hopefully keyword-only args become normalized and a future will come where I won't see `x.sum(0)` anymore VN On Sat, Sep 14, 2019 at 11:23 PM Thomas J Fan wrote: > +1 from me > > On Sat, Sep 14, 2019 at 8:12 AM Joel Nothman > wrote: > >> I am +1 for this change. >> >> I agree that

Re: [scikit-learn] Fit and predict method

Hi, The `classifier` object in your code _is_ the model. In other words, after `fit`, the classifier object will have some new attributes (for instance `classifier.coef_` in the case of linear models), which are used to make predictions when you call `predict`. Hope this helps, Vlad On Sun, Feb

Re: [scikit-learn] VOTE: scikit-learn governance document

+1 Thank you for the effort to formalize this! Best, Vlad On Mon, Feb 11, 2019, 02:47 Noel Dawe Hi Andy, > > +1 from me as well :) > > On Sun, Feb 10, 2019 at 8:54 PM Jacob Schreiber > wrote: > >> +1 from me as well. Thanks for putting in the time to write this all out. >> >> On Sun, Feb 10,

Re: [scikit-learn] New core dev: Joris Van den Bossche

Congratulations Joris, very well deserved! Vlad On Sat, Jun 23, 2018, 11:15 Sebastian Raschka wrote: > That's great news! I am glad to hear that you joined the project, Joris > Van den Bossche! I am a scikit-learn user (and sometimes contributor) and > really appreciate all the time and

Re: [scikit-learn] Contribution

On Mon, Jul 10, 2017 at 04:10:09PM +, federico vaggi wrote: > There is a fantastic library called lightning where the optimization > routines are first class citizens: > http://contrib.scikit-learn.org/lightning/ - you can take a look there. > However, lightning focuses on convex optimization,

Re: [scikit-learn] OMP ended prematurely due to linear dependence in the dictionary

8x42000). Is it even feasible >> to use OMP with such a big Matrix (even with ~120GB ram)? >> >> -Ben >> >> >> >> On 13.02.2017 23:31, Vlad Niculae wrote: >>> >>> Hi, >>> >>> Are the columns of your matrix normalized? Try set

Re: [scikit-learn] OMP ended prematurely due to linear dependence in the dictionary

Hi, Are the columns of your matrix normalized? Try setting `normalized=True`. Yours, Vlad On Mon, Feb 13, 2017 at 6:55 PM, Benjamin Merkt wrote: > Hi everyone, > > I'm using OrthogonalMatchingPursuit to get a sparse coding of a signal using > a dictionary

Re: [scikit-learn] Why do DTs have a different fit protocol than NB and SVMs?

e/tutorial/basic/tutorial.html On Tue, Dec 13, 2016 at 3:45 PM, Andreas Mueller <t3k...@gmail.com> wrote: > > > On 12/13/2016 03:38 PM, Vlad Niculae wrote: >> >> It is part of the API and enforced with tests, if I'm not mistaken. So you >> could use either form with

Re: [scikit-learn] Why do DTs have a different fit protocol than NB and SVMs?

It is part of the API and enforced with tests, if I'm not mistaken. So you could use either form with all sklearn estimators. Vlad On December 13, 2016 3:33:48 PM EST, Stuart Reynolds wrote: >I think he's asking whether returning the model is part of the API >(i.e.

Re: [scikit-learn] random forests using grouped data

I don't think there are any such estimators in scikit-learn directly, but the model selection machinery is there to help. Check out GroupKFold [1] so you can do cross-validation after concatenating all the samples, while ensuring that training and validation groups are separate. The setup of

Re: [scikit-learn] Bm25

it should only do this operation on >the non zero elements of the numerator. > >Sent from my iPhone > >> On Jul 1, 2016, at 5:36 PM, Vlad Niculae <zephy...@gmail.com> wrote: >> >> In the denominator you mean? It looks like you only need to add that >

Re: [scikit-learn] Bm25

it should only do this operation on >the non zero elements of the numerator. > >Sent from my iPhone > >> On Jul 1, 2016, at 5:36 PM, Vlad Niculae <zephy...@gmail.com> wrote: >> >> In the denominator you mean? It looks like you only need to add that >

Re: [scikit-learn] Bm25

>> >> >> Today's Topics: >> >> 1. Adding BM25 to scikit-learn.feature_extraction.text >> (Basil Beirouti) >> 2. Re: Adding BM25 to scikit-learn.feature_extraction.text >> (Vlad Niculae) >> >> >> >-