Mailman 3 November 2018 - scikit-learn

Next Sprint
by Andreas Mueller Jan. 10, 2019

Jan. 10, 2019

Hey folks. Are there any plans for a next sprint (in Paris/Europe?)? OpenML would like to join us next time and I think that would be cool. But they (and I ;) need some advance planning. I also have some funding that I could use for this as well. Cheers, Andy

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ANN Dirty_cat: learning on dirty categories
by Gael Varoquaux Dec. 19, 2018

Dec. 19, 2018

Hi scikit-learn friends, As you might have seen on twitter, my lab -with a few friends- has embarked on research to ease machine on "dirty data". We are experimenting on new encoding methods for non-curated string categories. For this, we are developing a small software project called "dirty_cat": https://dirty-cat.github.io/stable/ dirty_cat is a test bed for new ideas of "dirty categories". It is a research project, though we still try to do decent software engineering :). Rather than contributing to existing codebases (as the great categorical-encoding project in scikit-learn-contrib), we spanned it out in a separate software project to have the freedom to try out ideas that we might give up after gaining insight. We hope that it is a useful tool: if you have non-curated string categories, please give it a try. Understanding what works and what does not is important to know what to consolidate. Hopefully one day we can develop a tool that is of wide-enough interest that it can go in scikit-learn-contrib, or maybe even scikit-learn. Also, if you have suggestions of publicly available databases that we try it upon, we would love to hear from you. Cheers, Gaël PS: if you want to work on dirty-data problems in Paris as a post-doc or an engineer, send me a line

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Recurrent questions about speed for TfidfVectorizer
by Matthieu Brucher Dec. 5, 2018

Dec. 5, 2018

Hi all, I've noticed a few questions online (mainly SO) on TfidfVectorizer speed, and I was wondering about the global effort on speeding up sklearn. Is there something I can help on this topic (Cython?), as well as a discussion on this tough subject? Cheers, Matthieu -- Quantitative analyst, Ph.D. Blog: http://blog.audio-tk.com/ LinkedIn: http://www.linkedin.com/in/matthieubrucher

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[ANN] Scikit-learn 0.20.1 released
by Andreas Mueller Nov. 27, 2018

Nov. 27, 2018

Hey Everybody. I'm happy to announce that we released scikit-learn 0.20.1. This is a minor release containing mostly bugfixes and small improvements, though it's probably one of the bigger minor releases we've done. In particular there've been several enhancements to the ColumnTransformer, fetch_openml and parallelization with joblib. Another big change is that starting with this version we suggest users don't use the version of joblib that we include in scikit-learn and rather use joblib directly. You can find the full release notes here: https://scikit-learn.org/stable/whats_new.html#version-0-20-1 A big thank you to everybody who contributed! Best, Andy

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[ANN] Scikit-learn 0.20.1 released
by Andreas Mueller Nov. 27, 2018

Nov. 27, 2018

Hey Everybody. I'm happy to announce that we released scikit-learn 0.20.1. This is a minor release containing mostly bugfixes and small improvements, though it's probably one of the bigger minor releases we've done. In particular there've been several enhancements to the ColumnTransformer, fetch_openml and parallelization with joblib. Another big change is that starting with this version we suggest users don't use the version of joblib that we include in scikit-learn and rather use joblib directly. You can find the full release notes here: https://scikit-learn.org/stable/whats_new.html#version-0-20-1 A big thank you to everybody who contributed! Best, Andy

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Contrib: Artificial Immune Recongnition System
by AZZOUG Aghiles Nov. 26, 2018

Nov. 26, 2018

Hello devs, I'm a final year computer engineering student, currently doing my masters and engineering degree in recommender systems. Last summer, after an optimization course, I found a quite interesting recognition algorithm called : Artificial immune recognition system (described in the paper below), and I was wondering if its implementation would be interesting for the scikit-learn library. I wrote a first version of it which is available in my GitHub page ( https://github.com/AghilesAzzoug/Artificial-Immune-System <http://s.bl-1.com/h/ctT3Hlzb?url=https://github.com/AghilesAzzoug/Artificia…>), the code is only working for Iris datasets (since it was only a test). I'm happy to get any suggestions of critics from the community. Sincerely, Aghiles Paper ref. : Watkins, A., Timmis, J., & Boggess, L. (2004). Artificial immune recognition system (AIRS): An immune-inspired supervised learning algorithm. *Genetic Programming and Evolvable Machines*, *5*(3), 291-317.

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Re: [scikit-learn] make all new parameters keyword-only?
by Hanmin Qin Nov. 20, 2018

Nov. 20, 2018

I agree that this feature is advantageous and I'm +1 to apply it to new classes/functions, but for existing classes/functions, does it seem strange that only certain arguments are keyword only (i.e., some arguments can be specified by position, while others can't)? Hanmin Qin ----- Original Message ----- From: Andreas Mueller <t3kcit(a)gmail.com> To: scikit-learn(a)python.org Subject: [scikit-learn] make all new parameters keyword-only? Date: 2018-11-15 05:01 Hi all. Since we'll be dropping Python2.7 soon, we can now use keyword-only arguments. I would argue that whenever we add any argument anywhere, we should make it keyword-only from now on, with the exception of X and y (probably). What do others think? Are there other features in Python3 that we should consider adopting for 0.21? The reason for making arguments keyword-only is that a) users are force to write more readable code b) deprecations and api changes have less side-effects Cheers, Andy _______________________________________________ scikit-learn mailing list scikit-learn(a)python.org https://mail.python.org/mailman/listinfo/scikit-learn

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Re: [scikit-learn] Difference between CircleCI python2 and python3
by Hanmin Qin Nov. 19, 2018

Nov. 19, 2018

Thanks for the great PR.We're using matplotlib 3.0.1 (latest version) in python3 build and matplotlib 1.4.3 (minimal dependency) in python2 build.I think color="tab:blue" is not supported by matplotlib 1.X, so maybe you can try to use some simple colors. Hanmin Qin ----- Original Message ----- From: Oliver Rausch <oliverrausch99(a)gmail.com> To: scikit-learn(a)python.org Subject: [scikit-learn] Difference between CircleCI python2 and python3 Date: 2018-11-19 22:52 Hi all, I'm working on a PR [1] and the Circle python2 build [2] doesn't complete, while the python3 build does. Locally, building using "make html" also works. What is the difference between these two builds, and how could I locally debug the issue? Thanks, Oliver --- [1] https://github.com/scikit-learn/scikit-learn/pull/11682 [2] https://circleci.com/gh/scikit-learn/scikit-learn/38492 _______________________________________________ scikit-learn mailing list scikit-learn(a)python.org https://mail.python.org/mailman/listinfo/scikit-learn

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Difference between CircleCI python2 and python3
by Oliver Rausch Nov. 19, 2018

Nov. 19, 2018

Hi all, I'm working on a PR [1] and the Circle python2 build [2] doesn't complete, while the python3 build does. Locally, building using "make html" also works. What is the difference between these two builds, and how could I locally debug the issue? Thanks, Oliver --- [1] https://github.com/scikit-learn/scikit-learn/pull/11682 [2] https://circleci.com/gh/scikit-learn/scikit-learn/38492

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make all new parameters keyword-only?
by Andreas Mueller Nov. 14, 2018

Nov. 14, 2018

Hi all. Since we'll be dropping Python2.7 soon, we can now use keyword-only arguments. I would argue that whenever we add any argument anywhere, we should make it keyword-only from now on, with the exception of X and y (probably). What do others think? Are there other features in Python3 that we should consider adopting for 0.21? The reason for making arguments keyword-only is that a) users are force to write more readable code b) deprecations and api changes have less side-effects Cheers, Andy

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