🌐 Mailman 3 September 2019 - scikit-learn - python.org

Version 0.21! and plot_tree!
by Andrew Howe Dec. 5, 2019

Dec. 5, 2019

I want to say thank you to all the sklearn developers. The breadth and quality of this software is truly breathtaking. Specifically, I want to say thank you very very much for the plot_tree function! I have wasted a lot of effort in the past, on multiple OSes, getting everything to work so I could view the tree.export_graphviz results. Having this new function to plot the trees natively in matplotlib is extremely useful. Thanks again! Andrew <~~~~~~~~~~~~~~~~~~~~~~~~~~~> J. Andrew Howe, PhD LinkedIn Profile <http://www.linkedin.com/in/ahowe42> ResearchGate Profile <http://www.researchgate.net/profile/John_Howe12/> Open Researcher and Contributor ID (ORCID) <http://orcid.org/0000-0002-3553-1990> Github Profile <http://github.com/ahowe42> Personal Website <http://www.andrewhowe.com> I live to learn, so I can learn to live. - me <~~~~~~~~~~~~~~~~~~~~~~~~~~~>

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Can Scikit-learn decision tree (CART) have both continuous and categorical features?
by C W Oct. 6, 2019

Oct. 6, 2019

Hello all, I'm very confused. Can the decision tree module handle both continuous and categorical features in the dataset? In this case, it's just CART (Classification and Regression Trees). For example, Gender Age Income Car Attendance Male 30 10000 BMW Yes Female 35 9000 Toyota No Male 50 12000 Audi Yes According to the documentation https://scikit-learn.org/stable/modules/tree.html#tree-algorithms-id3-c4-5-…, it can not! It says: "scikit-learn implementation does not support categorical variables for now". Is this true? If not, can someone point me to an example? If yes, what do people do? Thank you very much!

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Website redesign
by Joel Nothman Sept. 26, 2019

Sept. 26, 2019

Hi scikit-learn users, Scikit-learn developer Thomas Fan recently gave our documentation and web site a refresh, targeting desktop and mobile devices. Please give it a try at https://scikit-learn.org/dev/ and raise usability issues at https://github.com/scikit-learn/scikit-learn/issues/new to help us get it ready for the next release. Congratulations to Thomas on some great work! Thanks all! Joel

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Normalizer, l1 and l2 norms
by Sole Galli Sept. 25, 2019

Sept. 25, 2019

Hello team, Quick question respect to the Normalizer(). My understanding is that this transformer divides the values (rows) of a vector by the vector euclidean (l2) or manhattan distances (l1). >From the sklearn docs, I understand that the Normalizer() does not learn the distances from the train set and stores them. It rathers normalises the data according to distance the data set presents, which could be or not, the same in test and train. Am I understanding this correctly? If so, what is the reason not to store these parameters in the Normalizer and use them to scale future data? If not getting it right, what am I missing? Many thanks and I will appreciate if you have an article on this to share. Cheers Sole

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Porting old MLPY KRR model to scikit-learn
by Chapman, James E Sept. 20, 2019

Sept. 20, 2019

Hello, I have some old KRR models from MLPY and I need to port those models over to a new code written with scikit-learn (transfer MLPY KRR data to a scikit-learn KernelRidge instance). Does anyone know if this is even possible, and if so, could you give me some suggestions as to how to accomplish it? Thanks and regards, James

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Vote on SLEP009: keyword only arguments
by Joel Nothman Sept. 18, 2019

Sept. 18, 2019

As per our Governance <http://scikit-learn.org/stable/governance.html> document, changes to API principles are to be established through an Enhancement Proposal (SLEP) from which any core developer can call for a vote on its acceptance. *SLEP009 Keyword Only Arguments is the first SLEP up for a vote. Please see* *https://scikit-learn-enhancement-proposals.readthedocs.io/en/latest/slep009/proposal.html <https://scikit-learn-enhancement-proposals.readthedocs.io/en/latest/slep009…>* *This proposal discusses the path to gradually forcing users to pass arguments, or most of them, as keyword arguments only.* Core developers are invited to vote on this change until 11 October 2019 by replying to this email thread. All members of the community are welcome to comment on the proposal on this mailing list, or to propose minor changes through Issues and Pull Requests at https://github.com/scikit-learn/enhancement_proposals/.

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Re: [scikit-learn] Vote on SLEP009: keyword only arguments
by Hanmin Qin Sept. 18, 2019

Sept. 18, 2019

I'll vote +1, though there're still lots of things to decide. Hanmin Qin ----- Original Message ----- From: Alexandre Gramfort <alexandre.gramfort(a)inria.fr> To: Scikit-learn mailing list <scikit-learn(a)python.org> Subject: Re: [scikit-learn] Vote on SLEP009: keyword only arguments Date: 2019-09-12 03:43 > But overall I'm + 1 on forcing kwargs for all __init__ methods. yes I think it will help for __init__ methods Alex PS : I don't shoot people (usually...) _______________________________________________ scikit-learn mailing list scikit-learn(a)python.org https://mail.python.org/mailman/listinfo/scikit-learn

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MultiBinarizer issue
by Sayak Paul Sept. 18, 2019

Sept. 18, 2019

I am working on a multi-label text classification problem. In order to encode the labels, I am using MultiLabelBinarizer. The labels of the dataset look like - [cs.AI, cs.CL, cs.CV, cs.NE, stat.ML][cs.CL, cs.AI, cs.LG, cs.NE, stat.ML][cs.CL, cs.AI, cs.LG, cs.NE, stat.ML][stat.ML, cs.AI, cs.CL, cs.LG, cs.NE][cs.CL, cs.AI, cs.LG, cs.NE, stat.ML] When I am using mlb = MultiLabelBinarizer() mlb.fit(labels)print(mlb.classes_) It gives me - array([' ', ',', '.', 'A', 'B', 'C', 'D', 'E', 'G', 'H', 'I', 'L', 'M', 'N', 'O', 'P', 'R', 'S', 'T', 'V', 'Y', '[', ']', 'a', 'c', 'h', 'm', 's', 't'], dtype=object) I (partially) fixed this problem by mlb.fit([y_train]) and I got (I printed first 10 classes) - array(['[cs.AI, cs.CC]', '[cs.AI, cs.CV]', '[cs.AI, cs.CY]', '[cs.AI, cs.DB]', '[cs.AI, cs.DS]', '[cs.AI, cs.GT]', '[cs.AI, cs.HC]', '[cs.AI, cs.IR]', '[cs.AI, cs.LG, stat.ML]', '[cs.AI, cs.LG]'], dtype=object) Ideally, it should output the individual classes (there may be something wrong in my code). When I am using mlb.fit_transform([y_train]), I am getting - array([[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]) Help would be very much appreciated. Here's the corresponding StackOverflow issue: https://stackoverflow.com/questions/57917936/multilabelbinarizer-gives-indi… Sayak Paul | sayak.dev

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Re: [scikit-learn] Monthly meetings between core developers
by Hanmin Qin Sept. 18, 2019

Sept. 18, 2019

I don't think it's worthwhile to worry too much about Beijing time if I'm the only person in Beijing. I'm happy to get up early once a month to learn from the great team! Hanmin Qin ----- Original Message ----- From: Alexandre Gramfort <alexandre.gramfort(a)inria.fr> To: Scikit-learn mailing list <scikit-learn(a)python.org> Subject: Re: [scikit-learn] Monthly meetings between core developers Date: 2019-07-18 17:16 hi, I kind of like the project boards we used for sprints: https://github.com/scikit-learn/scikit-learn/projects/11 the outcome of the core devs meeting could be to agree what should be listed on such a priority board. my 2c Alex On Thu, Jul 18, 2019 at 10:59 AM Olivier Grisel <olivier.grisel(a)ensta.org> wrote: > > I just found this planner to give it a try: > > https://www.timeanddate.com/worldclock/meetingtime.html?day=29&month=7&year… > > (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. The > least extreme timeslot for everybody to attend at the same time would > be: > > https://www.timeanddate.com/worldclock/meetingdetails.html?year=2019&month=… > > We could also arrange for a second timeslot later (that would be > Tuesday morning in Australia and China): > > https://www.timeanddate.com/worldclock/meetingdetails.html?year=2019&month=… > > I wouldn't mind doing a meeting around 11pm on Monday evening from > time to time but it would still be very early for Beijing. > > Just to let you know, I will be off from next Saturday till Monday > August 19 (big summer break :) so don't count on my for the first > meeting if you start the meetings in the mean time. > > Le jeu. 18 juil. 2019 à 00:15, Andreas Mueller <t3kcit(a)gmail.com> a écrit : > > > > > > > > On 7/17/19 2:17 PM, Guillaume Lemaître wrote: > > > I am +1. This is a great initiative. > > > > > > IMO, we could make it really regular (i.e., a specific week-day of a > > > specific week in a month), with a rolling time (for the time-zone issue). > > > In this matter, we could maybe clear more in advance our agenda > > > instead of trying to find a date which accommodates everyone. > > > > > I agree, we could do something like the last Monday every month and > > alternate between two (or three) different time zones. > > We have CET (UTC+1), EST (UTC-5), CT (UTC+08), AEDT (USC+11) so that > > seems super easy, right? > > (TIL CST can stand for "Central"/US, China, and Cuba! not confusing at all) > > > > I agree that we should be as inclusive as possible, but I also don't > > want to create the expectation that some people (not thinking of any > > Australian in particular) > > who already sacrifice a lot of their free time have to invest even more > > time to keep up with the rest. > > > > I think the idea of posting write-ups will help being more inclusive in > > that regard. > > _______________________________________________ > > scikit-learn mailing list > > scikit-learn(a)python.org > > https://mail.python.org/mailman/listinfo/scikit-learn > > > > -- > Olivier > http://twitter.com/ogrisel - http://github.com/ogrisel > _______________________________________________ > scikit-learn mailing list > scikit-learn(a)python.org > https://mail.python.org/mailman/listinfo/scikit-learn _______________________________________________ scikit-learn mailing list scikit-learn(a)python.org https://mail.python.org/mailman/listinfo/scikit-learn

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Problem regarding MultiLabelBinarizer
by Sayak Paul Sept. 14, 2019

Sept. 14, 2019

Sayak Paul | sayak.dev ---------- Forwarded message --------- From: <scikit-learn-request(a)python.org> Date: Fri, Sep 13, 2019 at 10:46 AM Subject: scikit-learn Digest, Vol 42, Issue 15 To: <scikit-learn(a)python.org> Send scikit-learn mailing list submissions to scikit-learn(a)python.org To subscribe or unsubscribe via the World Wide Web, visit https://mail.python.org/mailman/listinfo/scikit-learn or, via email, send a message with subject or body 'help' to scikit-learn-request(a)python.org You can reach the person managing the list at scikit-learn-owner(a)python.org When replying, please edit your Subject line so it is more specific than "Re: Contents of scikit-learn digest..." Today's Topics: 1. Re: scikit-learn Digest, Vol 42, Issue 14 (Sayak Paul) ---------------------------------------------------------------------- Message: 1 Date: Fri, 13 Sep 2019 10:46:09 +0530 From: Sayak Paul <spsayakpaul(a)gmail.com> To: scikit-learn(a)python.org Subject: Re: [scikit-learn] scikit-learn Digest, Vol 42, Issue 14 Message-ID: <CAGa_XGHgifW7W81-dVv3R3e80Nz2BVx=eWiKv52oRf-BS+RjXw(a)mail.gmail.com> Content-Type: text/plain; charset="utf-8" I was able to solve the problem using - mlb = MultiLabelBinarizer() mlb.fit([y_train]) Thanks for the suggestions. The output of mlb.classes_ now looks the following (first ten classes): [image: image.png] However, when I transform it using mlb.transform([y_train]), another problem arrises - [image: image.png] Kindly suggest :) Sayak Paul | sayak.dev On Thu, Sep 12, 2019 at 9:33 PM <scikit-learn-request(a)python.org> wrote: > Send scikit-learn mailing list submissions to > scikit-learn(a)python.org > > To subscribe or unsubscribe via the World Wide Web, visit > https://mail.python.org/mailman/listinfo/scikit-learn > or, via email, send a message with subject or body 'help' to > scikit-learn-request(a)python.org > > You can reach the person managing the list at > scikit-learn-owner(a)python.org > > When replying, please edit your Subject line so it is more specific > than "Re: Contents of scikit-learn digest..." > > > Today's Topics: > > 1. Re: MultiLabelBinarizer gives individual characters instead > of the classes (Lo?c Est?ve) > 2. Re: Vote on SLEP009: keyword only arguments (Guillaume Lema?tre) > 3. How can I enable line tracing for cython modules. > (Alejandro Javier Peralta Frias) > > > ---------------------------------------------------------------------- > > Message: 1 > Date: Thu, 12 Sep 2019 07:24:48 +0200 > From: Lo?c Est?ve <loic.esteve(a)ymail.com> > To: Scikit-learn mailing list <scikit-learn(a)python.org> > Subject: Re: [scikit-learn] MultiLabelBinarizer gives individual > characters instead of the classes > Message-ID: <vnokwoeeozmn.fsf(a)ymail.com> > Content-Type: text/plain; charset=utf-8 > > I think this caveat has been added in the dev doc (not yet in the stable > doc). You may want to read: > > https://scikit-learn.org/dev/modules/generated/sklearn.preprocessing.MultiL… > and in particular the part that starts with "A common mistake is to pass > in a list". > > Cheers, > Lo?c > > > Hi. > > > > I am working on a Multi-label text classification problem. In order to > encode the labels, I am using MultiLabelBinarizer. The labels of the > dataset look like - > > > > image > > > > When I am using > > > > mlb = MultiLabelBinarizer() > > mlb.fit(labels) > > print(mlb.classes_) > > > > I am getting - > > > > image > > > > Whereas, the output (sample output) I want is - > > > > image > > > > I got the above output by - > > > > mlb = MultiLabelBinarizer() > > sample_labels = [ > > ['stat.ML', 'cs.LG'], > > ['cs.CV', 'cs.RO'] > > ] > > mlb.fit(sample_labels) > > print(mlb.classes_) > > > > Help would be very much appreciated here. > > > > Here's the dataset I had prepared: > > arXivdata.csv.zip > > > > I stripped away the double quotes in the labels after loading it in a > pandas DataFrame by - > > > > import re > > > > arxiv_data['labels'] = arxiv_data['labels'].str.replace(r"[\"]", '') > > > > scikit-learn version: '0.21.3' > > > > Sayak Paul | sayak.dev > > > > ------------------------------ > > Message: 2 > Date: Thu, 12 Sep 2019 10:06:30 +0200 > From: Guillaume Lema?tre <g.lemaitre58(a)gmail.com> > To: Scikit-learn mailing list <scikit-learn(a)python.org> > Subject: Re: [scikit-learn] Vote on SLEP009: keyword only arguments > Message-ID: > < > CACDxx9jCkE5GAjRNj3TKinbuyWZQvXMrrcHBBqn6q_FXYdPrbQ(a)mail.gmail.com> > Content-Type: text/plain; charset="utf-8" > > To the question: do we want to utilise Python 3's force-keyword-argument > syntax > and to change existing APIs which support arguments positionally to use > this > syntax, via a deprecation period? > > I am +1. > > IMO, even if the syntax might be unknown, it will remain unknown until > projects > from the ecosystem are not using it. > > To the question: which methods should be impacted? > > I think we should be as gentle as possible at first. I am a little > concerned about > breaking some codes which were working fine before. > > On Thu, 12 Sep 2019 at 04:43, Joel Nothman <joel.nothman(a)gmail.com> wrote: > > > These there details of specific API changes to be decided: > > > > The question being put, as per the SLEP, is: > > do we want to utilise Python 3's force-keyword-argument syntax > > and to change existing APIs which support arguments positionally to use > > this syntax, via a deprecation period? > > _______________________________________________ > > scikit-learn mailing list > > scikit-learn(a)python.org > > https://mail.python.org/mailman/listinfo/scikit-learn > > > > > -- > Guillaume Lemaitre > INRIA Saclay - Parietal team > Center for Data Science Paris-Saclay > https://glemaitre.github.io/ >

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