Mailman 3 July 2023 - scikit-learn

[ANN] scikit-learn 0.24.0rc1 is online!
by Olivier Grisel Jan. 19, 2024

Jan. 19, 2024

Please help us test the first release candidate for scikit-learn 0.24.0: pip install scikit-learn==0.24.0rc1 Changelog: https://scikit-learn.org/0.24/whats_new/v0.24.html In particular, if you maintain a project with a dependency on scikit-learn, please let us know about any regression. Feel free to also retweet the announcement to get more people to test it before the final release (probably in 1 week or 2): https://twitter.com/scikit_learn/status/1334562221498753026 Thanks to anybody who helped make this happen! -- Olivier

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Using scikit-learn for homework.
by haxan aqarsu July 20, 2023

July 20, 2023

Hi sir/ madam I am a university student. If I use your scikit Learn code for my homework, do I need to write the authors who wrote these codes? I do not want to plagiarize. I really appreciate you if you reply my message. Kind regards,

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Subject: An error in an example
by עדו סוקולובסקי July 19, 2023

July 19, 2023

Good morning: I visited this web page to learn about sklearn.compose.ColumnTransformer https://scikit-learn.org/stable/modules/generated/sklearn.compose.ColumnTra… I copied the example in the bottom of the page to my Spider editor and executed it The final command resulted in this error message: -- בברכה עדו סוקולובסקי, 0544697279

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passing y to .transform() in pipeline
by Florin Andrei July 16, 2023

July 16, 2023

Any chance Pipeline will allow the target (y) to be passed to transformers? I'm not talking about transforming y, although that would be nice. I'm just talking about having y passed as an argument to transformers in the .transform() call. That would allow me to easily run my own target encoders. Currently, not having y available during .transform() is very restrictive. Thanks! -- Florin Andrei https://florin.myip.org/

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VOTE: adding a documentation team to the scikit-learn governance
by Adrin July 10, 2023

July 10, 2023

Hi, There's been a proposal to add a documentation team, and https://github.com/scikit-learn/scikit-learn/pull/26714 proposes the concrete changes. This is to recognize the work of people who have a focus on our documentation, as well as giving them the right tools and permissions to be more effective in their contributions. This is a call for a vote, and will be open for a month, concluding on August 10th. Discussions are welcome here or on the PR, and core contributors, as defined in our governance <https://scikit-learn.org/dev/governance.html#core-contributors> can cast their vote as an approval or a "request change" on the PR: https://github.com/scikit-learn/scikit-learn/pull/26714 Best, Adrin

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ANN: imbalanced-learn 0.11.0 released
by Guillaume Lemaître July 8, 2023

July 8, 2023

Hi all, We are happy to announce the 0.11.0 version of imbalanced-learn. imbalanced-learn is a toolbox aiming at providing a wide range of methods to cope with the problem of imbalanced data sets frequently encountered in machine learning and data mining. This release makes sure to be fully compatible with scikit-learn 1.0, 1.1, 1.2, and 1.3 pip install -U imbalanced-learn The conda-forge builds will be available shortly, which you can then install using: conda install -c conda-forge imbalanced-learn For more information, examples, and documentation, please visit: https:// imbalanced-learn.org Cheers, -- Guillaume Lemaitre Scikit-learn @ Inria Foundation https://glemaitre.github.io/

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New FOSS project powered by scikit-learn: tradero
by Matemática A3K July 3, 2023

July 3, 2023

tradero is a tool for achieving self-funding via trading. Self-funding means generating the means independently to cover a budget in order to opt by the value it produces rather than out of economic necessity. It tracks Symbols in an Exchange with a time resolution, calculates indicators and presents them in an useful way so the user can perform trading more effectively. The application is available at https://tradero.dev The full documentation is at https://tradero.readthedocs.io or the /docs directory. Community: * GitHub: https://github.com/math-a3k/tradero * Discord: https://discord.com/channels/1120602573607551049/1120602574488338505 * Mailing list: https://groups.google.com/g/tradero

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