From chandru3183 at gmail.com  Sat Jun  1 09:39:33 2024
From: chandru3183 at gmail.com (Chandrasekaran Ramachandran)
Date: Sat, 1 Jun 2024 19:09:33 +0530
Subject: [scikit-learn] Request for Scikit-learn Documentation Update -
 Decision Tree page
Message-ID: <CAHtKtqwvF6s6hSK+h9A1H45h-psXdeUwOvdg+5-qJkheucpZ-A@mail.gmail.com>

Hi Team,

 I am writing to bring to your attention a discrepancy in the documentation
on the scikit-learn web page
https://scikit-learn.org/stable/modules/tree.html

Specifically, the documentation currently highlights in red text that does
not support categorical variables for now.
However, my understanding and assumption were that it supports both
categorical and continuous variables.

*"scikit-learn uses an optimized version of the CART algorithm;
however, the scikit-learn implementation does not support categorical
variables for now."*


I also noticed that the example is provided on the same page for
categorical variables.
So, clarifying this information would greatly benefit users and enhance the
usability of your documentation.

If I am not wrong, please review and update the documentation?

Thanks in advance for your attention to this email.

Thanks and Regards,
Chandrasekaran R.
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From reshama.stat at gmail.com  Mon Jun  3 17:02:43 2024
From: reshama.stat at gmail.com (Reshama Shaikh)
Date: Mon, 3 Jun 2024 17:02:43 -0400
Subject: [scikit-learn] [ANN] scikit-learn 1.5.0 release
In-Reply-To: <ef9fa3eb-5e10-4d0d-b3de-173a83a039db@inria.fr>
References: <ef9fa3eb-5e10-4d0d-b3de-173a83a039db@inria.fr>
Message-ID: <CAKPCsui3U87ooW9OedL3wvks+ZC1RoeZWCvO-Y9BazGcWvsFNQ@mail.gmail.com>

Hello,

Following up on the recent release, there is a 12-minute video with
scikit-learn v1.5.0 Highlights available on the YouTube channel:
https://youtu.be/mOpU-zremz4

Video major topics include:
a) TunedThresholdClassifierCV class
>Among the new features, this new release introduces the
TunedThresholdClassifierCV class that can adjust the decision threshold of
any binary classifier to assign custom costs or gains to true/false
positives/negatives. This is especially powerful to implement
cost-sensitive learning, in particular when used in conjunction of
per-individual side-metadata used in the cost function, thanks to our
meta-data routing infrastructure.
(
https://scikit-learn.org/stable/auto_examples/model_selection/plot_cost_sensitive_learning.html#sphx-glr-auto-examples-model-selection-plot-cost-sensitive-learning-py
)

b) new pydata sphinx website theme highlights

---
Reshama Shaikh


On Tue, May 21, 2024 at 3:04?PM J?r?mie du Boisberranger <
jeremie.du-boisberranger at inria.fr> wrote:

> Hi everyone,
>
> We're happy to announce the 1.5.0 release which you can install via pip or
> conda:
>
>     pip install -U scikit-learn
>
> or
>
>     conda install -c conda-forge scikit-learn
>
>
> You can read the release highlights under
> https://scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_5_0.html
> and the long list of the changes under
> https://scikit-learn.org/stable/whats_new/v1.5.html
>
> This release also comes with a new theme for the https://scikit-learn.org
> website !
>
> This version supports Python versions 3.9 to 3.12.
>
> Thanks to all contributors who helped on 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
>
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