From lorentzen.ch at gmail.com Wed Sep 4 17:03:49 2024 From: lorentzen.ch at gmail.com (Christian Lorentzen) Date: Wed, 4 Sep 2024 23:03:49 +0200 Subject: [scikit-learn] ANN: model-diagnostics 1.2 released Message-ID: Dear scikit-learn community I am very glad to announce the release of model-diagnostics 1.2 with its new |plot_marginal| and |compute_marginal|. Model-diagnostics helps you to assess calibration and performance of most supervised model - be it machine learning or statistical - for point predictions (like the mean, a quantile, or the probability for binary classification). The focus is on visualization and user-friendliness while well backed by statistical theory. The new |plot_marginal|, for instance, gives a great overview of the calibration as well as the model effect by a single feature, see 1.2 release notes : image Best, Christian -------------- next part -------------- An HTML attachment was scrubbed... URL: From g.lemaitre58 at gmail.com Wed Sep 11 13:23:27 2024 From: g.lemaitre58 at gmail.com (=?UTF-8?Q?Guillaume_Lema=C3=AEtre?=) Date: Wed, 11 Sep 2024 19:23:27 +0200 Subject: [scikit-learn] [ANN] scikit-learn 1.5.2 is online! Message-ID: Hello everyone, We're happy to announce the 1.5.2 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-1-5-2 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 ! Guillaume, on behalf of the scikit-learn maintainers team. -------------- next part -------------- An HTML attachment was scrubbed... URL: From adrin.jalali at gmail.com Sun Sep 15 15:12:03 2024 From: adrin.jalali at gmail.com (Adrin) Date: Sun, 15 Sep 2024 21:12:03 +0200 Subject: [scikit-learn] Fwd: [SP] Standardized system for parameter management across Scientific Python libraries In-Reply-To: <01000191e53d1a2c-0b08d8e9-ccb2-4026-b405-0b4f3038ddac-000000@email.amazonses.com> References: <01000191e53d1a2c-0b08d8e9-ccb2-4026-b405-0b4f3038ddac-000000@email.amazonses.com> Message-ID: This sounds quite related to our parameter validation stuff. Thought I'd share. ---------- Forwarded message --------- From: Ewout ter Hoeven via Scientific Python < noreply at discuss.scientific-python.org> Date: Thu, Sep 12, 2024 at 9:57?AM Subject: Re: [SP] Standardized system for parameter management across Scientific Python libraries To: EwoutH September 12 Yes, a library might be the right implementation solution here. I was thinking of a spec to get the requirements and capabilities right for a wide set of repos, since this is not technically difficult to build (it?s can probably be just a dataclass with a few helper methods), but it?s difficult to get the format right and get everybody aligned. ------------------------------ Visit Topic or reply to this email to respond. You are receiving this because you enabled mailing list mode. To unsubscribe from these emails, click here . -------------- next part -------------- An HTML attachment was scrubbed... URL: