Mailman 3 June 2020 - scikit-learn

climate friendly software licence
by Sole Galli June 30, 2020

June 30, 2020

Hello Scikit-learn team, I've come across this: https://twitter.com/tristanharris/status/1277136696568508418?s=12 Basically, it is an initiative to include in software license a prohibition of use by fossil fuel extractivist companies. I would like to know your views on this? Is this something that you would pick up from Scikit-learn? Are there some legal concerns to be aware of? or anything else that should be considered? Because it sounds quite powerful and straightforward to me. I would be really keen to hear from you. Thanks a lot Sole

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Need some information regarding a GaussianNB package
by Saha, Prashanta June 29, 2020

June 29, 2020

Hi , I have been using your GaussianNB package for machine learning modeling by naive bayes algorithm. I have generated train and test set using scikit learn (set1). Then I modified that train and test set (set2) in a controlled way for my experiment. The classification should perform similarly (should return same class label for set1 and set2) according to the theory but it is behaving otherwise. Can you give me any insights why is this happening? Thanks, prashanta saha, PhD student, Montana State University,Bozeman,MT.

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scikit-learn monthly meeting June 29th : reminder
by Chiara Marmo June 26, 2020

June 26, 2020

Hi all, A reminder... :) The next scikit-learn monthly meeting will take place on Monday June 29th at 12PM UTC: https://www.timeanddate.com/worldclock/meetingdetails.html?year=2020&month=… While these meetings are mainly for core-devs to discuss the current topics, we are also happy to welcome non-core devs and other project maintainers. Feel free to join, using the following link: https://meet.google.com/xhq-yoga-rtf If you plan to attend and you would like to discuss something specific about your contribution please add your name (or github pseudo) in the " Contributors <https://hackmd.io/iJjuPx3QTQ6AqDLiPVmHFg?both#Contributors>" section, of the public pad: https://hackmd.io/iJjuPx3QTQ6AqDLiPVmHFg *@core devs, please make sure to update your notes.* Best, Chiara

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scikit-learn monthly meeting June 29th
by Chiara Marmo June 22, 2020

June 22, 2020

Hi all, The next scikit-learn monthly meeting will take place on Monday June 29th at 12PM UTC: https://www.timeanddate.com/worldclock/meetingdetails.html?year=2020&month=… While these meetings are mainly for core-devs to discuss the current topics, we are also happy to welcome non-core devs and other project maintainers. Feel free to join, using the following link: https://meet.google.com/xhq-yoga-rtf If you plan to attend and you would like to discuss something specific about your contribution please add your name (or github pseudo) in the " Contributors <https://hackmd.io/iJjuPx3QTQ6AqDLiPVmHFg?both#Contributors>" section, of the public pad: https://hackmd.io/iJjuPx3QTQ6AqDLiPVmHFg *@core devs, please make sure to update your notes before the week-end.* Best, Chiara

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Sensitivity analysis PR proposal
by Pamphile Roy June 20, 2020

June 20, 2020

Hi, Is there a wish to have sensitivity analysis? Currently we can measure the quality of a regressor’s output with a metric, but there is nothing to on the parameter side. It would be handy to have sensitivity measures of the input parameters on the output. Namely: Sobol’ indices (most used). I have some starting code already https://github.com/tupui/otsensitivity <https://github.com/tupui/otsensitivity> and https://github.com/tupui/batman/blob/master/batman/visualization/density.py <https://github.com/tupui/batman/blob/master/batman/visualization/density.py>. Sobol' (first order and total). COSI indices. CUSUNORO. Moment independent measures. Some visualization functions. Let me know if there is interest for a PR and if yes, what shall I include :) Pamphile @tupui

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Permission to publish
by DELSO, GASPAR (ICCV) June 19, 2020

June 19, 2020

Hi, We were wondering whether it would be possible to reproduce one figure from your Users' Guide in a publication. Who would be the right contact person for this? Best regards Gaspar Delso

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ANN: imbalanced-learn 0.7 released
by Christos Aridas June 16, 2020

June 16, 2020

Hi all, We're happy to announce the 0.7 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 should be fully compatible with scikit-learn 0.23 The full changelog can be found here: http://imbalanced-learn.org/stable/whats_new.html The new release of imbalanced-learn is already available via pip and conda! For more information, examples, and documentation, please visit our website: http://imbalanced-learn.org Cheers, Chris, on behalf of the imbalanced-learn team.

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Fwd: Question regarding regression models
by Kelden Dorji June 11, 2020

June 11, 2020

Hi scikit-learn, I have a question related to regression models. Please find my question in the link below. I am still new to this and would appreciate any help. Thank you and have a nice day! https://stackoverflow.com/questions/62325079/issues-with-regression-model-g… Kelden Dradul Dorji

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Gaussian Process Regression with multiple features
by Apu Sarkar June 2, 2020

June 2, 2020

Apu Sarkar <apusarkar(a)gmail.com> [image: image.gif] 1:32 PM (2 hours ago) [image: image.gif] [image: image.gif] to scikit-learn [image: image.gif] Hi, I am trying to predict a target (DeltaNDT) which is dependent on five features (Cu, Ni, P, T, Fluence). Please check the ipython notebook and the csv input data: https://github.com/apusarkar/GP-Regression gpr.predict is generating predictions for the train data. However, with test_preds = gpr.predict(X_test) all values test_preds are zeros. Please help me to find the mistake in my approach. Thanks.

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Gaussian Process Regression with multiple features
by Apu Sarkar June 2, 2020

June 2, 2020

Hi, I am trying to predict a target (DeltaNDT) which is dependent on five features (Cu, Ni, P, T, Fluence). Please find attached the ipython notebook and the csv input data. gpr.predict is generating predictions for the train data. However, with test_preds = gpr.predict(X_test) all values test_preds are zeros. Please help me to find the mistake in my approach. Thanks. Apu

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