[scikit-learn] scikit-learn Digest, Vol 98, Issue 1
Mukesh Muthiyan
mukeshmuthiyan at gmail.com
Wed Jul 3 13:09:01 EDT 2024
U
On Wed, Jul 3, 2024, 21:30 <scikit-learn-request at python.org> wrote:
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> Today's Topics:
>
> 1. [ANN] scikit-learn 1.5.1 is online! (J?r?mie du Boisberranger)
> 2. Re: [ANN] scikit-learn 1.5.1 is online! (Guillaume Lema?tre)
> 3. Skrub 0.2.0: tabular learning made easy (Gael Varoquaux)
> 4. Re: [ANN] scikit-learn 1.5.1 is online! (Gael Varoquaux)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Wed, 3 Jul 2024 11:23:17 +0200
> From: J?r?mie du Boisberranger <jeremie.du-boisberranger at inria.fr>
> To: scikit-learn at python.org
> Subject: [scikit-learn] [ANN] scikit-learn 1.5.1 is online!
> Message-ID: <e0ef2dd6-723b-4f9b-8e9d-1593665b3d97 at inria.fr>
> Content-Type: text/plain; charset=UTF-8; format=flowed
>
> Hello everyone,
>
> We're happy to announce the 1.5.1 release !
>
>
> It contains fixes for a few regressions introduced in 1.5.
>
> You can see the changelog here:
> https://scikit-learn.org/stable/whats_new/v1.5.html#version-1-5-1
>
>
> You can upgrade with pip as usual:
>
> ```
> pip install -U scikit-learn
> ```
>
> The conda-forge builds can be installed using:
>
> ```
> conda install -c conda-forge scikit-learn
> ```
>
>
> Thanks to everyone who contributed to this release !
>
> J?r?mie, on behalf of the Scikit-learn maintainers team.
>
>
>
> ------------------------------
>
> Message: 2
> Date: Wed, 3 Jul 2024 11:28:31 +0200
> From: Guillaume Lema?tre <g.lemaitre58 at gmail.com>
> To: Scikit-learn mailing list <scikit-learn at python.org>
> Subject: Re: [scikit-learn] [ANN] scikit-learn 1.5.1 is online!
> Message-ID:
> <CACDxx9hovH3CydHOkOAQ1yWXBJJqntkF5pt+OjL6Lx=
> xUtTpiw at mail.gmail.com>
> Content-Type: text/plain; charset="utf-8"
>
> Thanks J?r?mie for this one.
>
> On Wed, 3 Jul 2024 at 11:26, J?r?mie du Boisberranger <
> jeremie.du-boisberranger at inria.fr> wrote:
>
> > Hello everyone,
> >
> > We're happy to announce the 1.5.1 release !
> >
> >
> > It contains fixes for a few regressions introduced in 1.5.
> >
> > You can see the changelog here:
> > https://scikit-learn.org/stable/whats_new/v1.5.html#version-1-5-1
> >
> >
> > You can upgrade with pip as usual:
> >
> > ```
> > pip install -U scikit-learn
> > ```
> >
> > The conda-forge builds can be installed using:
> >
> > ```
> > conda install -c conda-forge scikit-learn
> > ```
> >
> >
> > Thanks to everyone who contributed to this release !
> >
> > J?r?mie, on behalf of the Scikit-learn maintainers team.
> >
> > _______________________________________________
> > scikit-learn mailing list
> > scikit-learn at python.org
> > https://mail.python.org/mailman/listinfo/scikit-learn
> >
>
>
> --
> Guillaume Lemaitre
> Open source engineer at :probabl.
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> ------------------------------
>
> Message: 3
> Date: Wed, 3 Jul 2024 15:04:48 +0200
> From: Gael Varoquaux <gael.varoquaux at normalesup.org>
> To: Scikit-learn user and developer mailing list
> <scikit-learn at python.org>
> Subject: [scikit-learn] Skrub 0.2.0: tabular learning made easy
> Message-ID:
> <j4gq2kqbqffb5qisbqxfwturrqt2bun5udo4avue5lifla2zjt at sqtnsnwljhwg>
> Content-Type: text/plain; charset=iso-8859-1
>
> Hi scikit-learn'ers
>
> We just released skrub 0.2.0: https://skrub-data.org. This release
> markedly simplifies learning on complex dataframes.
>
> # `model = tabular_learner('classifier')`
>
> The highlight of the release is the `tabular_learner` function, which
> facilitates creating pipelines that readily perform machine learning on
> dataframes, adding preprocessing to a scikit-learn compatible learner. The
> function basically packs defaults and heuristics to transform all forms of
> dataframes to a representation that is well suited to a learner, and it can
> adapt these transformation:
> tabular_learner(HistGradientBoostingClassifier()) encodes categories
> differently than tabular_learner(LogisticRegression()).
>
> The heuristics are tuned based on much benchmarking and experience shows
> that they give good tradeoffs. The default `tabular_learner('classifier')`
> is often a strong baseline.
>
>
> # `transformer = TableVectorizer()`
>
> Behind the hood, the work is done by the `skrub.TableVectorizer()`, a
> scikit-learn compatible transformer that facilitates combining multiple
> transformations on the different columns of a dataframe. The
> TableVectorizer is not new in the 0.2.0 release, but we have completely
> revamped its internals to cover really well edge cases. Indeed, one
> challenge is to make sure that nothing different or strange happens at test
> time. Actually, enforcing consistency between train-time and test-time
> transformation is the real value of skrub compared to using pandas or
> polars to do transformation.
>
> # Increasing support of polars
>
> We have implemented a new mechanism for supporting both pandas and polars.
> It has not been applied on all the codebase, hence the support is still
> imperfect. However, we are seeing increasing support for polars in skrub,
> and our goal in the short term is to provide rock-solid polar support.
>
> Try skrub out! It's still young, but in mind opinion, it provides a lot of
> value to tabular learning.
>
> Cheers,
>
> Ga?l
>
>
> ------------------------------
>
> Message: 4
> Date: Wed, 3 Jul 2024 14:53:00 +0200
> From: Gael Varoquaux <gael.varoquaux at normalesup.org>
> To: Scikit-learn mailing list <scikit-learn at python.org>
> Subject: Re: [scikit-learn] [ANN] scikit-learn 1.5.1 is online!
> Message-ID:
> <bpvuwgcoyzumjrh5mkfcfwj4hr57woshhmzumuqdecc57tflr5 at ypis73ehtv4h>
> Content-Type: text/plain; charset=iso-8859-1
>
> On Wed, Jul 03, 2024 at 11:28:31AM +0200, Guillaume Lema?tre wrote:
> > Thanks J?r?mie for this one.
>
> +1! Thanks heaps, it's a lot of work, but so much value to the users!
>
> Ga?l
>
> > On Wed, 3 Jul 2024 at 11:26, J?r?mie du Boisberranger <[1]
> > jeremie.du-boisberranger at inria.fr> wrote:
>
> > Hello everyone,
>
> > We're happy to announce the 1.5.1 release !
>
>
> > It contains fixes for a few regressions introduced in 1.5.
>
> > You can see the changelog here:
> > [2]https://scikit-learn.org/stable/whats_new/v1.5.html#version-1-5-1
>
>
> > You can upgrade with pip as usual:
>
> > ```
> > pip install -U scikit-learn
> > ```
>
> > The conda-forge builds can be installed using:
>
> > ```
> > conda install -c conda-forge scikit-learn
> > ```
>
>
> > Thanks to everyone who contributed to this release !
>
> > J?r?mie, on behalf of the Scikit-learn maintainers team.
>
> > _______________________________________________
> > scikit-learn mailing list
> > [3]scikit-learn at python.org
> > [4]https://mail.python.org/mailman/listinfo/scikit-learn
> --
> Gael Varoquaux
> Research Director, INRIA
> http://gael-varoquaux.info http://twitter.com/GaelVaroquaux
>
>
> ------------------------------
>
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> ------------------------------
>
> End of scikit-learn Digest, Vol 98, Issue 1
> *******************************************
>
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