Re: [scikit-learn] Welcome to the moved scikit-learn mailing list.

Thanks for making it happen! -- Olivier ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn

Re: [scikit-learn] NB-SVM Implementation

I think it could be implemented as a preprocessing step: this is the approach followed by: https://github.com/ryankiros/skip-thoughts/blob/master/eval_classification.py Note that in that case LogisticRegression is used as the final classifier instead of a squared hinge loss SVM but that should not

Re: [scikit-learn] partial_fit implementation for IsolationForest

> However, at present, IsolationForest only fits data in batch even while it > may be well suited to incremental on-line learning since one could subsample > recent history and older estimators can be dropped progressively. What you describe is quite different from what sklearn models typically

Re: [scikit-learn] GradientBoostingRegressor with training, validation, and test set.

It means that in your script you should print the score on the validation set instead of the test set. Then you are allowed to tweak the values in your params dict to see if you can find values that improve that score. Once you are confident that you can no longer improve the validation score via

Re: [scikit-learn] GradientBoostingRegressor with training, validation, and test set.

GridSearchCV will automatically generate the validation sets internally (this is where the "CV" comes from). So you don't have to generate a validation set if you decide to use GridSearchCV to select the best model. More details here: http://scikit-learn.org/stable/model_selection.html -- Olivi

Re: [scikit-learn] How to test on PYTHON_ARCH=32 with mac?

> I believe this `arch -i386` only works as a prefix for Python.org Python, > but I'm happy to be corrected. Then the following should work: arch -i386 python -c "import nose; nose.main()" sklearn ___ scikit-learn mailing list scikit-learn@python.org

Re: [scikit-learn] 0.18?

Sorry for the late reply, Before working on this release I would like to automate the wheel generation process (for the release wheels) in a single repo that will generate wheels for linux, osx and windows based on https://github.com/matthew-brett/multibuild I plan to put that repo under https://

Re: [scikit-learn] 0.18?

Thanks Matthew I had not realized. I will add an appveyor config there with a dedicated `sklearn-wheels` account so that we don't wait for the `sklearn-ci` jobs when we are building the release wheels. -- Olivier ___ scikit-learn mailing list scikit-lea

Re: [scikit-learn] 0.18?

Ok I fixed all the 32 bit Linux & OSX build issues in scikit-learn master and all wheels builds are green with the multibuild setup: https://travis-ci.org/MacPython/scikit-learn-wheels Matthew: would you be interested in having the multibuild repo extended to also include appveyor configration fi

Re: [scikit-learn] Building Scikit Learn in Win 7 64bits

The error message mentions gcc. Have you installed some mingw version? As of now our windows build is only properly tested with the Visual Studio C++ compiler from appveyor: https://ci.appveyor.com/project/sklearn-ci/scikit-learn I have not tested the build with mingwpy in a while (I am not a wi

Re: [scikit-learn] 0.18?

Ok for pushing back. Let's try to work on the beta on the week after euroscipy if we can. At least all the annoying binary packaging issues are fixed (test failures for the linux and OSX 32 bit platforms) so the release process itself should hopefully be painless. -- Olivier

Re: [scikit-learn] Latent Semantic Analysis (LSA) and TrucatedSVD

I am not sure this is exactly the same because we do not center the data in the TruncatedSVD case (as opposed to the real PCA case where whitening is the same as calling StandardScaler). Having an option to normalize the transformed data by sigma seems like a good idea but we should probably not c

Re: [scikit-learn] Latent Semantic Analysis (LSA) and TrucatedSVD

BTW Roman, the examples in your gist would make a great non-regression test for this new feature. Please feel free to submit a PR. -- Olivier ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn

Re: [scikit-learn] Declaring numpy and scipy dependencies?

I would be +1 to add the dependencies to numpy and scipy on the binary wheels only. We don't have the tools yet but this could be implemented in the auditwheel tool that is already used to generate the manylinux1 compatible wheels for Linux. -- Olivier ___

Re: [scikit-learn] Mailing list "slow"?

I have not noticed it myself. Let me try to time this email to check: sent at 3:01pm CEST. ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn

Re: [scikit-learn] Mailing list "slow"?

It's already in the archive: https://mail.python.org/pipermail/scikit-learn/2016-September/000495.html -- Olivier ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn

Re: [scikit-learn] Contribution project proposal

If this is your first contribution to the project, I would strongly suggest to start by contributing a small bug fix or improvement to get accustomed to the kind of things the core devs expect when reviewing a PR. Also please read the contributors guide : http://scikit-learn.org/dev/developers/co

Re: [scikit-learn] out of core in ARD or Bayessian Ridge Regression

I don't think anybody is working on this but you should better check in github pull requests. Best, -- Olivier ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn

Re: [scikit-learn] HashingVectorizer slow in version 0.18

I cannot reproduce such a degradation on my machine: (sklearn-0.17)ogrisel@is146148:~/code/scikit-learn$ python ~/tmp/bench_vectorizer.py scikit-learn 0.17.1. Numpy 1.11.2. Python 3.5.0 x86_64 Vectorizing 20newsgroup 11314 documents Vectorization completed in 4.033604383468628 seconds, resulting

Re: [scikit-learn] HashingVectorizer slow in version 0.18

That's really weird. I don't have a windows machine handy at the moment. It would be nice if someone else could confirm. Could you please run the Python profiler on this to see where the time is spent on the slow setup? -- Olivier ___ scikit-learn mail

Re: [scikit-learn] Development workflow proposal: merge master instead of rebasing

If it works, +1 on my side. I think I have never used `git merge --rebase` in the past. -- Olivier ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn

Re: [scikit-learn] modifying CV score

You can indeed derive from BaseEstimator and implement fit, predict and optionally score. Here is the documentation for the expected estimator API: http://scikit-learn.org/stable/developers/contributing.html#apis-of-scikit-learn-objects As this is a linear regression model, you can also want to

[scikit-learn] Preparing a scikit-learn 0.18.2 bugfix release

Hi all, I think we should release 0.18.2 to get some important fixes and make it easy to release Python 3.6 wheel package for all the operating systems using the automated procedure. I identified a couple of PR to backport to 0.18.X to prepare the 0.18.2 release. Are there any other important rec

Re: [scikit-learn] Preparing a scikit-learn 0.18.2 bugfix release

In retrospect, making a small 0.19 release is probably a good idea. I would like to get https://github.com/scikit-learn/scikit-learn/pull/8002 in before cutting the 0.19.X branch. -- Olivier Grisel ___ scikit-learn mailing list scikit-learn@python.org

Re: [scikit-learn] Preparing a scikit-learn 0.18.2 bugfix release

I would rather like to get it out before April ideally and instead of setting up a roadmap I would rather just identify bugs that are blockers and fix only those and don't wait for any feature before cutting 0.19.X. -- Olivier ___ scikit-learn mailing l

Re: [scikit-learn] Permutation-test-score

This is non-parametric (aka brute force) way to check that a model has a predictive performance significantly higher than chance. For models with 90% accuracy this is useless as we already know for sure that the model is better than predicting at random. This method is only useful if you have very

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

It's ok to work on a bug if the original contributor has not replied to the reviewers comments in a while (e.g. a couple of weeks). -- Olivier ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn

Re: [scikit-learn] Modelling event rates

I don't think we have any model dedicated to this, but it's possible that expressive non-parametricmodels such as RF and GBRT or richly parameterized models such as MLP with a regression loss can do a good enough job at giving you a point estimate. -- Olivier _

Re: [scikit-learn] GSOC call for mentors

Personally I don't feel like mentoring this year. I would really like to focus my scikit-learn time on finishing the joblib process refactoring with Thomas Moreau and the binning / thread-based parallelization of boosted trees with Guillaume and Raghav. -- Olivier

Re: [scikit-learn] Logistic regression with elastic net regularization

Note that SGD is not very good at optimizing finely with a non-smooth penalty (e.g. l1 or elasticnet). The future SAGA solver is going to be much better at finding the optimal sparsity support (although this support is not guaranteed to be stable across re-sampling of the training set if the traini

Re: [scikit-learn] Logistic regression with elastic net regularization

>From a generalization point of view (test accuracy), the optimal sparsity support should not matter much though, but it can be helpful to find a the optimally sparsest solution for either computational constraints (smaller models with a lower prediction latency) and interpretation of the weights (

Re: [scikit-learn] decision trees

For large enough models (e.g. random forests or gradient boosted trees ensembles) I would definitely recommend arbitrary integer coding for the categorical variables. Try both, use cross-validation and see for yourself. -- Olivier ___ scikit-learn mail

Re: [scikit-learn] decision trees

Integer coding will indeed make the DT assume an arbitrary ordering while one-hot encoding does not force the tree model to make that assumption. However in practice when the depth of the trees is not too limited (or if you use a large enough ensemble of trees), the model will have enough flexibil

Re: [scikit-learn] XGboost Classifier error

Please provide the full traceback. Without it it's impossible to tell whether the problem is in scikit-learn or xgboost. Also, please provide a minimal reproduction script as explained in: http://scikit-learn.org/stable/faq.html#what-s-the-best-way-to-get-help-on-scikit-learn-usage -- Olivier _

Re: [scikit-learn] Broken c dependencies

Thanks Matthew, I have uploaded your Python 3.6 wheel for MacOSX to PyPI. -- Olivier ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn

Re: [scikit-learn] develop install with pip?

+1 for recommending to use `pip install --editable .`. -- Olivier ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn

Re: [scikit-learn] Query about use of standard deviation on tree feature_importances_ in demo plot_forest_importances.html

+1 for changing this example to have error bars represent 5 & 95 percentiles or 25 and 75 percentiles (quartiles). Or event bootstrapped confidence intervals or the mean feature importance for each variable. This might be a bit too verbose for an example though. > Perhaps more importantly - is a

[scikit-learn] Scikit-learn workshop and sprint at EuroScipy 2017 in Erlangen

Hi all, FYI I have just submitted a 90 min tutorial on scikit-learn to the EuroScipy CFP. If anybody is interested in co-teaching / TA-ing this workshop please let me know. I also plan to stay for the one-day sprint to help people make their first contribution to the project. Last year we had gre

Re: [scikit-learn] Scikit-learn workshop and sprint at EuroScipy 2017 in Erlangen

Hi Tim, Thanks for the help. I was planning to do a quick sklearn intro based on slides such as the first part of: https://speakerdeck.com/ogrisel/intro-to-scikit-learn-and-whats-new-in-0-dot-17 (but I would like to re-do them in HTML with remark.js as I do here: https://github.com/ogrisel/decks

Re: [scikit-learn] Agglomerative clustering

You can have a look at the test named "test_agglomerative_clustering" in: https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/cluster/tests/test_hierarchical.py -- Olivier ___ scikit-learn mailing list scikit-learn@python.org https://mail.

Re: [scikit-learn] Scikit-learn at Data Intelligence this past weekend

Thanks for this report! -- Olivier ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn

Re: [scikit-learn] Fwd: [SciPy-User] EuroSciPy 2017 call for contributions - extension of deadline

I am pretty sure this is exactly the kind of presentation that the EuroScipy audience would enjoy. Please submit! -- Olivier ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn

Re: [scikit-learn] Typo in online documentation on Matrix Factorization

2017-07-06 15:10 GMT+02:00 Olivier Grisel : > (and just make sure that the "components" is a synonym for "dictionary > atoms" in the literature). Actually I meant: and just make sure that our documentation states explicitly that the "components" is a s

Re: [scikit-learn] Typo in online documentation on Matrix Factorization

I think the documentation is correct. U, a.k.a. "the code" or "the activations" has shape (n_samples, n_components) and V a.k.a. "the dictionary" or "the components" has shape (n_components, n_features) in both case. We could use n_components uniformly instead of n_atoms for consistency's sake (an

Re: [scikit-learn] Which algorithm is used in sklearn SGDClassifier when modified huber loss is used?

The name of the algorithm / model would be "L2-penalized linear model with modified Huber loss trained with Stochastic Gradient Descent". SVM is traditionally used to describe models that use the hinge loss only (or sometimes the squared hinge loss too). Only the log loss can be lead to a probabi

Re: [scikit-learn] Help with NLP

Please use this mailing list if you have targeted scikit-learn mailing list questions. Otherwise you should better ask a specific question on an NLP and datascience community platform such as: https://datascience.stackexchange.com/questions/tagged/nlp or if you have a programming related question

Re: [scikit-learn] Contribution - Markov Clustering

If this is the first time you contribute, please make sure to carefully read the contributors guide till the end: http://scikit-learn.org/stable/developers/contributing.html In particular, make sure to follow the estimators API conventions for your PR to get a chance to be reviewed. In particular

[scikit-learn] scikit-learn 0.19b2 is available for testing

The new release is coming and we are seeking feedback from beta testers! pip install scikit-learn==0.19b2 conda-forge packages should follow in the coming hours / days. Note that many models have changed behaviors and some things have been deprecated, see the full changelog at: http://scikit-

Re: [scikit-learn] Extra trees tuning parameters

I believe so even though it's always better to check in the code to see how this parameter is actually used. -- Olivier ​ ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn

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 de

[scikit-learn] scikit-learn 0.19.0 is out!

Grab it with pip or conda ! Quoting the release highlights from the website: We are excited to release a number of great new features including neighbors.LocalOutlierFactor for anomaly detection, preprocessing.QuantileTransformer for robust feature transformation, and the multioutput.ClassifierCh

Re: [scikit-learn] scikit-learn-commits mailing list defunct?

+1 ​ ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn

Re: [scikit-learn] scikit-learn-commits mailing list defunct?

+1 for python.org if they accept this kind of mailing lists. ​ ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn

Re: [scikit-learn] New core devs: Hanmin Qin, Guillaume Lemaître, and Roman Yurchak

Congrats to all three of you! Thank you very much for your contributions and in particular in reviewing contributions by others. -- Olivier ​ ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn

Re: [scikit-learn] Rapid Outlier Detection via Sampling

> Do I need to write object oriented or are functions also ok? I you want to contribute an implementation as a new project on scikit-learn contrib, you should be careful to follow the scikit-learn estimators API: http://scikit-learn.org/dev/developers/contributing.html#apis-of-scikit-learn-object

Re: [scikit-learn] Error while running 'python setup.py build_ext --inplace'

Maybe update your version of Cython? -- Olivier ​ ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn

Re: [scikit-learn] Announcing sklearn-xarray

Interesting project! BTW, do you know about dask-ml [1]? It might be interesting to think about generalizing the input validation of fit and predict / transform as a private method of the BaseEstimator class instead of directly calling into sklearn.utils.validation functions so has to make it eas

Re: [scikit-learn] clustering on big dataset

Have you had a look at BIRCH? http://scikit-learn.org/stable/modules/clustering.html#birch -- Olivier ​ ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn

Re: [scikit-learn] Announcing modAL: a modular active learning framework

It looks nice, thanks for sharing. Do you plan to couple the active learner with a UX-optimized labeling interface (for instance with a react.js or similar frontend and a flask or similar backend)? -- Olivier ​ ___ scikit-learn mailing list scikit-lear

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

Hi everyone! Let's welcome Joris Van den Bossche (@jorisvdbossche) officially as a scikit-learn core developer! Joris is one of the maintainers of the pandas project and recently contributed many new great PRs to scikit-learn (notably the ColumnTransformer and a refactoring of the categorical var

Re: [scikit-learn] sklearn Pipeline decorators

That's a cool trick but I am worried it would render our API too "frameworky" for my taste. I think the FunctionTransformer is enough: http://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.FunctionTransformer.html ___ scikit-learn maili

Re: [scikit-learn] Bootstrapping in sklearn

This looks like a very useful project. There is also scikits-bootstraps [1]. Personally I prefer the flat package namespace of resample (I am not a fan of the 'scikits' namespace package) but I still think it would be great to contact the author to know if he would be interested in joining efforts

Re: [scikit-learn] Bootstrapping in sklearn

I believe it would fit in sklearn-contrib even if it's more for statistical inference rather than machine learning style prediction. Others might disagree. Anyways, joining efforts to improve documentation, CI, testing and so on is always a good thing for your future users. -- Olivier _

Re: [scikit-learn] [ANN] Scikit-learn 0.20.0

Joy ! ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn

Re: [scikit-learn] [ANN] Scikit-learn 0.20.0

Le mer. 26 sept. 2018 à 23:02, Joel Nothman a écrit : > And for those interested in what's in the pipeline, we are trying to draft > a roadmap... > https://github.com/scikit-learn/scikit-learn/wiki/Draft-Roadmap-2018 > > But there are no doubt many features that are absent there too. > Indeed, i

Re: [scikit-learn] [ANN] Scikit-learn 0.20.0

> > > > I think model serialization should be a priority. > There is also the ONNX specification that is gaining industrial adoption and that already includes open source exporters for several families of scikit-learn models: https://github.com/onnx/onnxmltools -- Olivier __

Re: [scikit-learn] Random Forest Regressor -- Implementation in C++

You might also want to have a look at https://github.com/onnx/onnxmltools although I am not sure if there are RF optimized ONNX runtimes at this point. -- Olivier ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listi

Re: [scikit-learn] Next Sprint

We can also do Paris in April / May or June if that's ok with Joel and better for Andreas. I am teaching on Fridays from end of January to March. But I can miss half a day of sprint to teach my class. -- Olivier ___ scikit-learn mailing list scikit-lea

Re: [scikit-learn] make all new parameters keyword-only?

+1 on the ideal in general (and to enforce this on new classes / params). +1 to be conservative and not break existing code. Le mar. 20 nov. 2018 à 21:09, Joris Van den Bossche < jorisvandenboss...@gmail.com> a écrit : > Op zo 18 nov. 2018 om 11:14 schreef Joel Nothman : > >> I think we're all ag

Re: [scikit-learn] benchmarking TargetEncoder Was: ANN Dirty_cat: learning on dirty categories

Maybe a subset of the criteo TB dataset? ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn

Re: [scikit-learn] New core dev: Adrin Jalali

Congrats and welcome Adrin! -- Olivier ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn

Re: [scikit-learn] Difference between linear model and tree-based regressor?

They are very different statistical models from a mathematical point of view. See the online scikit-learn documentation or reference text books such as "Elements of Statistical Learning" for more details. In practice, linear model tends to be faster to fit on large data, especially when the number

Re: [scikit-learn] MLPClassifier on WIndows 10 is 4 times slower than that on macOS?

You should probably just "conda update scikit-learn": scikit-learn 0.20.1 is available on the official anaconda channel for all supported operating systems: https://anaconda.org/anaconda/scikit-learn -- Olivier ___ scikit-learn mailing list scikit-learn

Re: [scikit-learn] Next Sprint

ople say that they > >> > might be available at this time. It is good for many people, or > should we > >> > organize a doodle? > >> > > >> > G > >> > > >> > On Wed, Dec 19, 2018 at 05:27:21PM -0500, Andreas Mueller wrote: &

Re: [scikit-learn] Sprint discussion points?

I would also add generalizing early stopping options to most estimators. This is a bit related to Joel's point on max_iter consistency in LogisticRegression. -- Olivier ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailm

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

+1 ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn

Re: [scikit-learn] Release Candidate for Scikit-learn 0.21

\o/ ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn

[scikit-learn] ANN: scikit-learn 0.21.2 released

A quick bugfix release to fix a critical regression in the computation of the euclidean distances returning incorrect values silently. This release also includes other bugfixes listed in the changelog: https://scikit-learn.org/0.21/whats_new.html#version-0-21-2 The PyPI.org wheels and conda-forg

Re: [scikit-learn] [Copyright] Skicit-learn graphic

I think it's ok to do as you said. -- Olivier ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn

Re: [scikit-learn] Scikit Learn in a Cray computer

How many cores du you have on this machine? joblib.cpu_count() ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn

Re: [scikit-learn] Scikit Learn in a Cray computer

You have to use a dedicated framework to distribute the computation on a cluster like you cray system. You can use mpi, or dask with dask-jobqueue but the also need to run parallel algorithms that are efficient when running in a distributed with a high cost for communication between distributed wo

[scikit-learn] New core developer: jeremiedbb

The core developers of Scikit-learn have recently voted to welcome Jérémie Du Boisberranger to the team, in recognition of his efforts and trustworthiness as contributor. Jérémie's works at Inria Saclay and is supported by the scikit-learn initiative at Fondation Inria and its partners. Congratula

Re: [scikit-learn] Monthly meetings between core developers

+1 for last Monday of each month. How about the duration? 1h max + breakout in smaller groups on more specific topics if needed? ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn

Re: [scikit-learn] Monthly meetings between core developers

Le jeu. 18 juil. 2019 à 08:29, Adrin a écrit : > > BTW, where was the meeting for last Monday organized? I don't think I knew it > was happening. I do not understand what you are referring to. My email was about the organization of future meetings as suggested by Andreas. ___

Re: [scikit-learn] Monthly meetings between core developers

I just found this planner to give it a try: https://www.timeanddate.com/worldclock/meetingtime.html?day=29&month=7&year=2019&p1=240&p2=33&p3=37&p4=179&iv=0 (Berlin and Paris are on the same timezone so I did not put only Berlin). It's going to be challenging to find a timeslot for every body. Th

Re: [scikit-learn] scikit-learn twitter account

Le mar. 5 nov. 2019 à 12:46, Gael Varoquaux a écrit : > > On Mon, Nov 04, 2019 at 10:14:26PM -0700, Andreas Mueller wrote: > > Should we re-purpose the existing twitter account or make a new one? > > https://twitter.com/scikit_learn > > I think that we should repurpose it: > > - Make a "scikit-lea

Re: [scikit-learn] scikit-learn twitter account

Le ven. 15 nov. 2019 à 17:31, Nicolas Hug a écrit : > > What's the status of this? Would be great to have it for the 0.22 release :) ! > +1 and we could also announce / thank / RT new sources of funding (CZI and Fujitsu). ___ scikit-learn mailing list s

Re: [scikit-learn] scikit-learn twitter account

I am not sure who has the rights to manage the twitter account. I just sent a password reset request to "sc**@a..***" I suspect that this is Andreas but I am not so sure. ___ scikit-learn mailing list scikit-learn@python.org https:

Re: [scikit-learn] scikit-learn twitter account

Thanks Tom, let me try to configure this. -- Olivier ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn

Re: [scikit-learn] scikit-learn twitter account

Ok, I have sent some invites. I would like to create @sklearn_commits instead of @scikit_learn_commits that is too long to my taste. Any opinion? -- Olivier ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/

Re: [scikit-learn] scikit-learn twitter account

Le ven. 22 nov. 2019 à 17:24, Gael Varoquaux a écrit : > > > I would like to create @sklearn_commits instead of > > @scikit_learn_commits that is too long to my taste. Any opinion? > > Some people do not make the link between "sklearn" and "scikit-learn" :) People who are likely to follow a twitt

Re: [scikit-learn] scikit-learn twitter account

I have created the https://twitter.com/sklearn_commits twitter account. I have applied to make this account a "Twitter Developer" account to be able to use https://github.com/filearts/tweethook to register it as a webhook for the main scikit-learn github repo. Once ready, I will remove the old we

Re: [scikit-learn] scikit-learn twitter account

Alright, it seems that I can create twitter apps (and generates API tokens) for the @sklearn_commits account however https://github.com/filearts/tweethook does not work as it relies on a third party webtask,io service that does not accept any new subscription... I am looking for an alternative way

Re: [scikit-learn] scikit-learn twitter account

It might actually be possible to use github actions with https://github.com/xorilog/twitter-action for instance. I will try to give it a try with a test repo. -- Olivier ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailm

Re: [scikit-learn] scikit-learn twitter account

Alright, I have configured the new github action for the tweets on @sklearn_commits: https://github.com/scikit-learn/scikit-learn/pull/15758 I tested it from my repo and it worked fine (I deleted the test tweet though). We can do the switch as soon as this PR is merged. -- Olivier _

Re: [scikit-learn] scikit-learn twitter account

Ok the twitter accounts are now switched: https://twitter.com/scikit_learn/status/1201794032650932224 The notifications for commits pushed to master are live: https://twitter.com/sklearn_commits Ready for the release :) -- Olivier ___ scikit-learn m

Re: [scikit-learn] Paris Sprint in January and wiki update

Indeed I do not see the "circle add" button in the tweetdeck UI anymore. But it's ok not to prepare the threads before tweeting the first tweet. We can build the thread progressively by publishing the first tweet and then replying one tweet after the other by hitting the reply button of the last p

[scikit-learn] scikit-learn 0.22.1 is out!

This is a minor release that includes many bug fixes and solves a number of packaging issues with Windows wheels in particular. Here is the full changelog: https://scikit-learn.org/stable/whats_new/v0.22.html#version-0-22-1 The conda package will follow soon (hopefully). Thank you very much to a

Re: [scikit-learn] Monthly meetings

I get a message for an invalid meeting id. -- Olivier ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn

Re: [scikit-learn] ANN scikit-learn 0.23.0 release

Congrats on the release! And thank you very much to all those who were involved in making it happen (and Adrin in particular)! -- Olivier ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn

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