Re: [scikit-learn] The culture of commit squashing

We could stop squashing during development, and use the *new* Squash-and-Merge button on GitHub. What do you think? Tom 2016-06-14 8:06 GMT+02:00 Matthieu Brucher : > I don't even think that squashing them before the merge is actually sound. > Y

Re: [scikit-learn] The culture of commit squashing

@Andreas It's a bit hidden: You need to click on "Merge pull-request", then do *not* click on "Confirm merge", but on the small arrow to the right, and select "Squash and merge". 2016-06-14 18:13 GMT+02:00 Andreas Mueller : > I'm +1 for using the button when appropriate. > I think it should be up

Re: [scikit-learn] Using fit_intercept with sparse matrices

note2: The LogisticRegression and Ridge(solver='sag') code do fit the intercept without breaking sparsity. For other solvers in Ridge, in the case of a sparse X input, the solver will automatically be changed to 'sag' and raise a warning. Tom 2016-07-04 7:24 GMT+02:00 Tom Dupré la Tour : > not

Re: [scikit-learn] Does NMF optimise over observed values

If X is sparse, explicit zeros and missing-value zeros are **both** considered as zeros in the objective functions. Changing the objective function wouldn't need a new interface, yet I am not sure the code change would be completely trivial. The question is: do we want this new objective function

Re: [scikit-learn] nmf with multiple cores

Hi Roberto, As answered previously, there is no multi-threading available for NMF in scikit-learn. However, if you want to compute *multiple* NMF in parallel, you can use joblib with a threading backend, as the 'cd' solver releases the GIL (through cython code) during a large part of the time. Th

Re: [scikit-learn] n_jobs for LogisticRegression

Hi, In LogisticRegression, n_jobs is only used for one-vs-rest parallelization. In LogisticRegressionCV, n_jobs is used for both one-vs-rest and cross-validation parallelizations. So in LogisticRegression with multi_class='multinomial', n_jobs should have no impact. The docstring should probably

Re: [scikit-learn] Need help to start contributing

Welcome! If you're looking to get started, you might try sorting issues by those with "Needs contributor" and "easy" to begin with. https://github.com/scikit-learn/scikit-learn/issues?q=is%3Aopen+is%3Aissue+label%3AEasy+label%3A%22Need+Contributor%22 You should also check out the contributor guide

Re: [scikit-learn] question about class_weights in LogisticRegression

The class weights and sample weights are used in the same way, as a factor specific to each sample, in the loss function. In LogisticRegression, it is equivalent to incorporate this factor into a regularization parameter C specific to each sample. Tom 2017-08-01 18:30 GMT+02:00 Johnson, Jeremiah

Re: [scikit-learn] Inconsistencies in clustering documentations

Hi Anaël, Thanks for spotting these inconsistencies. You are very welcome to open pull-requests and/or issues on the GitHub tracker (cf. http://scikit-learn.org/stable/developers/contributing.html#contributing-code ) The documentation issue should be straightforward. The parameter renaming would n

Re: [scikit-learn] Probabilities for LogisticRegression and LDA

*The set of independent regressions described in Wikipedia is *not* an OvR model.* It is just a (weird) way to understand the multinomial logistic regression model. OvR logistic regression and multinomial logistic regression are two different models. In multinomial logistic regression as a set of

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

+1 as well Le lun. 11 févr. 2019 à 10:23, Nelle Varoquaux a écrit : > +1 > > On Mon, 11 Feb 2019 at 10:16, Roman Yurchak via scikit-learn < > scikit-learn@python.org> wrote: > >> +1 as well >> >> Roman >> >> On 11/02/2019 09:47, Gael Varoquaux wrote: >> > +1 on my side too. >> > >> > Thanks a lo

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

I vote +1 Tom Le lun. 16 sept. 2019 à 06:30, Joel Nothman a écrit : > Btw, consensus is defined by 2/3 of cast votes by core devs, according to > our Governance. https://scikit-learn.org/dev/about.html#authors lists 20 > core devs. > > That is, we could consider this resolved after 14 votes in

Re: [scikit-learn] Vote: Add Adrin Jalali to the scikit-learn technical committee

+1 Le lun. 27 avr. 2020, à 07 h 00, Alexandre Gramfort < alexandre.gramf...@inria.fr> a écrit : > +1 > ___ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.org/mailman/listinfo/scikit-learn > __