From reshama.stat at gmail.com Wed Nov 2 07:51:39 2022 From: reshama.stat at gmail.com (Reshama Shaikh) Date: Wed, 2 Nov 2022 07:51:39 -0400 Subject: [scikit-learn] Pandas DataFrame output is now available for all sklearn transformers In-Reply-To: References: Message-ID: Hello, We have uploaded a new video, with better sound, on the topic of: Pandas DataFrame output is now available for all sklearn transformers https://youtu.be/5bCg8VfX2x8 (The previous video is now unlisted, so the link is not broken.) Thank you for your patience. --- Reshama Shaikh she/her On Thu, Oct 27, 2022 at 3:39 PM Reshama Shaikh wrote: > Hello, > > Pandas DataFrame output is now available for all sklearn transformers (in > dev version 1.2)! This will make running pipelines on data frames much > easier, and provides better ways to track feature names. > > There is a 14-minute video with examples, some more information and some > FAQs answered at the end [a]. > > This is one of the biggest improvements in scikit-learn in a long time and > we'd love your feedback! Please try out the nightly built and give it a go. > We'd love to hear both about whether this helps your use cases and any bugs > you find. > > A special thanks to the maintainers: Thomas J. Fan, Guillaume LeMaitre, > Christian Lorentzen ! > > [a] video > https://youtu.be/J4KCu9WWDTo > > [b] example > > https://scikit-learn.org/dev/auto_examples/miscellaneous/plot_set_output.html#sphx-glr-auto-examples-miscellaneous-plot-set-output-py > > [c] LinkedIn post > > https://www.linkedin.com/feed/update/urn:li:activity:6987027021608460289/?actorCompanyId=79865351 > > --- > Reshama Shaikh > she/her > > -------------- next part -------------- An HTML attachment was scrubbed... URL: From etfredeluces at up.edu.ph Tue Nov 8 02:02:59 2022 From: etfredeluces at up.edu.ph (Ellarizza Fredeluces) Date: Tue, 8 Nov 2022 16:02:59 +0900 Subject: [scikit-learn] Inquiry on evolutionary/genetic algorithms Message-ID: Dear Scikit-learn enthusiasts and developers, I am new in optimization and machine learning in general. I am having a hard time. So I have an objective function y = a*x**3 + b*x**2 + c*x + d I have values for x and y and I would want to determine a,b, c,d using GA. I am confused with number of inputs and number of population. Should i match the population size with my number of inputs (x,y)? For example, I have 100 sets of x, y. Should I also have 100 as population size? Thank you. Sincerely, Ella -------------- next part -------------- An HTML attachment was scrubbed... URL: From loic.esteve at ymail.com Tue Nov 8 02:22:28 2022 From: loic.esteve at ymail.com (=?utf-8?B?TG/Dr2MgRXN0w6h2ZQ==?=) Date: Tue, 08 Nov 2022 08:22:28 +0100 Subject: [scikit-learn] Deprecation of the 'sklearn' PyPI package starts December 1st References: Message-ID: Hi everyone, "pip install scikit-learn" has always been the supported way to install scikit-learn with pip, but for some time, "pip install sklearn" has been working too. The scikit-learn team has decided to gradually deprecate the 'sklearn' PyPI package by doing a brownout over one year: - starting December 1st 2022, using 'sklearn' rather than 'scikit-learn' for pip commands will start to raise an error over some predefined time windows - these time windows durations will gradually increase over one year - on December 1st 2023, using 'sklearn' rather than 'scikit-learn' for pip commands will always raise an error More information about the 'sklearn' package deprecation is available at https://github.com/scikit-learn/sklearn-pypi-package. Any concerns about this, let us know by replying to this email or by creating an issue at https://github.com/scikit-learn/sklearn-pypi-package/issues/new. Cheers, Lo?c From fernando.wittmann at gmail.com Thu Nov 10 14:29:09 2022 From: fernando.wittmann at gmail.com (Fernando Marcos Wittmann) Date: Thu, 10 Nov 2022 16:29:09 -0300 Subject: [scikit-learn] VotingRegressor with pretrained estimators from CV as input Message-ID: Hello, I'm dealing with a problem without much data. As a solution, I'm training 10 estimators using a 10-Fold CV-Schema. Now, I wanted to persist those models. In order to avoid having to save 10 estimators, I was thinking about saving a single VotingRegressor with those pre-trained models or maybe writing a custom estimator to be used only for inference. Has anyone dealt with similar problems? TLDR: Looking for an easy way to store multiple models created using cross-validation as a single model. More context: I'll be using mlflow sklearn autolog, so it will be waaay more convenient to log only a single model instead of multiple models in each experiment. Thanks! -------------- next part -------------- An HTML attachment was scrubbed... URL: From g.lemaitre58 at gmail.com Thu Nov 17 03:56:14 2022 From: g.lemaitre58 at gmail.com (=?UTF-8?Q?Guillaume_Lema=C3=AEtre?=) Date: Thu, 17 Nov 2022 09:56:14 +0100 Subject: [scikit-learn] ANN: New member in the Contributor Experience Team Message-ID: We are excited to welcome a new member to the Contributor Experience Team: - Tim Head: https://github.com/betatim Looking forward to furthering interactions within the scikit-learn community. On the behalf of the scikit-learn team. -- Guillaume Lemaitre Scikit-learn @ Inria Foundation https://glemaitre.github.io/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From thomasjpfan at gmail.com Fri Nov 18 10:19:36 2022 From: thomasjpfan at gmail.com (Thomas J. Fan) Date: Fri, 18 Nov 2022 09:19:36 -0600 Subject: [scikit-learn] scikit-learn monthly developer meeting: Monday November 28, 2022 Message-ID: Dear all, The scikit-learn developer monthly meeting will take place on Monday November 28 at 15:00 UTC. - Video call link: https://meet.google.com/gmn-acub-mrr - Meeting notes / agenda: https://hackmd.io/0yokz72CTZSny8y3Re648Q - Local times: https://www.timeanddate.com/worldclock/meetingdetails.html?year=2022&month=11&day=28&hour=15&min=0&sec=0&p1=1440&p2=240&p3=248&p4=195&p5=179&p6=224 The goal of this meeting is to discuss ongoing development topics for the project. Everybody is welcome. As usual, please follow the code of conduct of the project: https://github.com/scikit-learn/scikit-learn/blob/main/CODE_OF_CONDUCT.md Regards, Thomas -------------- next part -------------- An HTML attachment was scrubbed... URL: From adrin.jalali at gmail.com Fri Nov 18 12:04:15 2022 From: adrin.jalali at gmail.com (Adrin) Date: Fri, 18 Nov 2022 18:04:15 +0100 Subject: [scikit-learn] VotingRegressor with pretrained estimators from CV as input In-Reply-To: References: Message-ID: Hi, It's easy to write a meta-estimator and store it. You can write one for yourself in a few lines of code. This might help: https://github.com/adrinjalali/talks/blob/master/2022/sklearn-estimator-ODSC/custom_estimators_solved.ipynb On Thu, Nov 10, 2022 at 8:30 PM Fernando Marcos Wittmann < fernando.wittmann at gmail.com> wrote: > Hello, > > I'm dealing with a problem without much data. As a solution, I'm training > 10 estimators using a 10-Fold CV-Schema. Now, I wanted to persist those > models. In order to avoid having to save 10 estimators, I was thinking > about saving a single VotingRegressor with those pre-trained models or > maybe writing a custom estimator to be used only for inference. Has anyone > dealt with similar problems? > > TLDR: Looking for an easy way to store multiple models created using > cross-validation as a single model. > > More context: I'll be using mlflow sklearn autolog, so it will be waaay > more convenient to log only a single model instead of multiple models in > each experiment. > > Thanks! > _______________________________________________ > scikit-learn mailing list > scikit-learn at python.org > https://mail.python.org/mailman/listinfo/scikit-learn > -------------- next part -------------- An HTML attachment was scrubbed... URL: From loic.esteve at ymail.com Mon Nov 28 03:13:40 2022 From: loic.esteve at ymail.com (=?utf-8?B?TG/Dr2MgRXN0w6h2ZQ==?=) Date: Mon, 28 Nov 2022 09:13:40 +0100 Subject: [scikit-learn] Deprecation of the 'sklearn' PyPI package starts December 1st In-Reply-To: References: Message-ID: Hi everyone, a reminder that using sklearn rather than scikit-learn in pip commands, for example "pip install sklearn", will start failing in three days (December 1st) over some predefined time windows. More information about the 'sklearn' package deprecation is available at https://github.com/scikit-learn/sklearn-pypi-package. Cheers, Lo?c > Hi everyone, > > "pip install scikit-learn" has always been the supported way to install > scikit-learn with pip, but for some time, "pip install sklearn" has been > working too. > > The scikit-learn team has decided to gradually deprecate the 'sklearn' > PyPI package by doing a brownout over one year: > - starting December 1st 2022, using 'sklearn' rather than 'scikit-learn' > for pip commands will start to raise an error over some predefined > time windows > - these time windows durations will gradually increase over one year > - on December 1st 2023, using 'sklearn' rather than 'scikit-learn' for > pip commands will always raise an error > > More information about the 'sklearn' package deprecation is available at > https://github.com/scikit-learn/sklearn-pypi-package. > > Any concerns about this, let us know by replying to this email or by > creating an issue at > https://github.com/scikit-learn/sklearn-pypi-package/issues/new. > > Cheers, > Lo?c From jeremie.du-boisberranger at inria.fr Tue Nov 29 05:36:46 2022 From: jeremie.du-boisberranger at inria.fr (Jeremie du Boisberranger) Date: Tue, 29 Nov 2022 11:36:46 +0100 Subject: [scikit-learn] [ANN] scikit-learn 1.2.0rc1 is online! In-Reply-To: <5f1f099d-371a-3127-8bff-dc51d6439cce@inria.fr> References: <5f1f099d-371a-3127-8bff-dc51d6439cce@inria.fr> Message-ID: Hi everyone, Please help us test the first release candidate for scikit-learn 1.2.0: ?? pip install scikit-learn==1.2.0rc1 Changelog:https://scikit-learn.org/1.2/whats_new/v1.2.html In particular, if you maintain a project with a dependency on scikit-learn, please let us know about any regression. Thanks to everyone who contributed to this release! Best, J?r?mie From olivier.grisel at ensta.org Tue Nov 29 06:00:11 2022 From: olivier.grisel at ensta.org (Olivier Grisel) Date: Tue, 29 Nov 2022 12:00:11 +0100 Subject: [scikit-learn] [ANN] scikit-learn 1.2.0rc1 is online! In-Reply-To: References: <5f1f099d-371a-3127-8bff-dc51d6439cce@inria.fr> Message-ID: Thanks Jeremie for pushing this release out! Now is the time to test downstream projects against this to make sure it will not break too many things when we publish the 1.2.0 final release in a week or two ! -- Olivier From jeremie.du-boisberranger at inria.fr Wed Nov 30 10:42:39 2022 From: jeremie.du-boisberranger at inria.fr (Jeremie du Boisberranger) Date: Wed, 30 Nov 2022 16:42:39 +0100 Subject: [scikit-learn] Deleting old RCs from PyPI In-Reply-To: <5f1f099d-371a-3127-8bff-dc51d6439cce@inria.fr> References: <5f1f099d-371a-3127-8bff-dc51d6439cce@inria.fr> Message-ID: Hi everyone, During the last release we reached our project limit size on PyPI. Although we've been able to increase this limit, we thought that it would be a good idea to make some space. As a first step, we plan to remove all release candidates (RCs) of previous releases. These should not be downloaded by anyone at this point. If you need these old RCs, please tell us quickly before we delete them because it will be permanent. We also plan to remove all releases but the last from testpypi. Same, if you need them please tell us quickly. Have a good day, J?r?mie