🌐 Mailman 3 February 2019 - scikit-learn - python.org

AUCROC/MAP confidence intervals in scikit
by Stuart Reynolds Feb. 7, 2019

Feb. 7, 2019

https://papers.nips.cc/paper/2645-confidence-intervals-for-the-area-under-t… Does scikit (or other Python libraries) provide functions to measure the confidence interval of AUROC scores? Same question also for mean average precision. It seems like this should be a standard results reporting practice if a method is available. - Stuart

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Possible bug in BayesianGaussianMixture?
by Stefan Ulbrich Feb. 7, 2019

Feb. 7, 2019

Hello, I think I might have found a bug in the BayesianGaussianMixture–or at least encountered a behavior that I was not expecting. The problem occurs when having clusters with small extent (in my case, it is 2D geographic data) that are far away from each other. While the means and their number are determined correctly, the co-variance matrices are not (at least compared to the regular GMM): They are are much wider and point towards the mean of the cluster centers. A minimal example and visualization can be seen on a stackoverflow question I opened. https://stackoverflow.com/q/54524283 So my question is whether the results of GMM and BGMM should be similar or this is the expected behavior (and why)? Thanks in advance for an answer and best wishes Stefan

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Scikit-learn porting strategy
by Laurent Julliard Feb. 6, 2019

Feb. 6, 2019

Hi everyone, If one were to start porting scikit-learn to another language what would be the plan to follow? I'm looking for directions that would say something like a) start with foundational components (e.g. numpy I guess) b) then port module A for a quick win, c) follow with modules B, C... d) the address the scipy dependent modules... Thank you for your help and advice. Eljay -- Laurent Julliard

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SciPy 2019 Conference - 10 days left for submissions, registration now open
by Paul Ivanov Feb. 5, 2019

Feb. 5, 2019

SciPy 2019, the 18th annual Scientific Computing with Python conference, will be held July 8-14, 2019 in Austin, Texas. The annual SciPy Conference brings together over 800 participants from industry, academia, and government to showcase their latest projects, learn from skilled users and developers, and collaborate on code development. The call for abstracts for SciPy 2019 for talks, posters and tutorials is now open. The original deadline for submissions has been extended and the new deadline is February 15, 2019. Conference Website: https://www.scipy2019.scipy.org/ Submission Website: https://easychair.org/conferences/?conf=scipy2019 *Talks and Posters (July 10-12, 2019)* In addition to the general track, this year will have specialized tracks focused on: - Data Driven Discoveries (including Machine Learning and Data Science) - Open Source Communities (Sustainability) *Mini Symposia* - Science Communication through Visualization - Neuroscience and Cognitive Science - Image Processing - Earth, Ocean, Geo and Atmospheric Science There will also be a SciPy Tools Plenary Session each day with 2 to 5 minute updates on tools and libraries. *Tutorials (July 8-9, 2019)* Tutorials should be focused on covering a well-defined topic in a hands-on manner. We are looking for useful techniques or packages, helping new or advanced Python programmers develop better or faster scientific applications. We encourage submissions to be designed to allow at least 50% of the time for hands-on exercises even if this means the subject matter needs to be limited. Tutorials will be 4 hours in duration. In your tutorial application, you can indicate what prerequisite skills and knowledge will be needed for your tutorial, and the approximate expected level of knowledge of your students (i.e., beginner, intermediate, advanced). Instructors of accepted tutorials will receive a stipend. -- _ / \ A* \^ - ,./ _.`\\ / \ / ,--.S \/ \ / `"~,_ \ \ __o ? _ \<,_ /:\ --(_)/-(_)----.../ | \ --------------.......J Paul Ivanov http://pirsquared.org | GPG/PGP key id: 0x0F3E28F7

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sklearn.cluster.OPTICS
by Mohit Srivastava Feb. 4, 2019

Feb. 4, 2019

Dear all, I want to use your clustering algorithm "sklearn.cluster.OPTICS". But it is not working and found that it's not available at the moment( found on the internet). Could you please help me with the issue? When would it be possible to use it? Please reply as soon as possible. thanks regards Mohit Srivastava

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Does model consider about previous training results after reloading model and then training with new data?
by lampahome Feb. 1, 2019

Feb. 1, 2019

As title, I'm confused. If I reload model and train with new data, what happened? 1st train old data -> save model -> reload -> train with new data Does the 2nd training will consider about previous training results? Or just a new result with new data?

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