🌐 Mailman 3 April 2021 - scikit-learn - python.org

[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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Open Source: sustainability and etiquette
by Reshama Shaikh Oct. 11, 2021

Oct. 11, 2021

Hello, I've seen some excellent resources that have explained open source, its sustainability, challenges and *indirectly, the etiquette*. I am starting to compile the list here [a]. This keynote by Stuart Geiger is a must-watch: The Invisible Work of Maintaining & Sustaining Open Source Software [b] There is one more video by Emily someone who was at Microsoft, but is now a professor somewhere, and I am trying to track that video down. I think it's from 2017. I'll add it to the list once I find it. If anyone knows the full name of the speaker, please share. [a] https://www.dataumbrella.org/open-source/open-source-sustainability [b] https://www.youtube.com/watch?v=PM3iltcaIL8 Best, Reshama --- Reshama Shaikh she/her Blog <https://reshamas.github.io> | Twitter <https://twitter.com/reshamas> | LinkedIn <https://www.linkedin.com/in/reshamas/> | GitHub <https://github.com/reshamas> Data Umbrella <https://www.dataumbrella.org> NYC PyLadies <https://meet.meetup.com/wf/click?upn=pEEcc35imY7Cq0tG1vyTt6zEs68RbcMfjPcajN…>

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Spanish translation proposal for Scikit-Learn documentation
by Mariangela Petrizzo Aug. 17, 2021

Aug. 17, 2021

Dear Scikit-Learn team! I am Mariángela Petrizzo, I am writing to you as a member of Qu4nt, a team dedicated to the use of open source tools for the development of software solutions with emphasis on data science. We have a strong interest in translating the Scikit-Learn documentation into Spanish. Our team is made up of members from various scientific fields, including some university faculty in linguistics and computer sciences, with a wide experience in Python as well as several libraries used for data analysis and machine learning, and also contribute locally as evangelists of its use in Spanish-speaking communities, in particular, the leader initiated the translation of some Software Carpentry lessons into Spanish. That is why we have been discussing the opportunity to offer our contribution to the Python project, promoting the translation into Spanish of the documentation of some of the libraries with the greatest impact in our areas of interest. Talking with David Mertz, to whom we are sending a copy of this email, we have explored options, and the idea of working with Scikit-learn has really seemed to be an exceptional opportunity for all of us and the community. He's very enthusiastic about the idea of generating a spanish translation of Scientific Python libraries like Scikit-learn. For us, this translation project has to be done through a completely open work on Github, taking as reference the restructured text sources for Sphinx from a git fork, using the tools provided by Sphinx itself for internationalization: https://www.sphinx-doc.org/en/1.8/intl.html, and applying tags to perform planned updates. In addition, as with any open source project, the main mechanism for quality assurance comes from the users themselves who will have the channels available for submitting issues. Our intention is to secure all the infrastructure and mechanisms to make this possible: making the process transparent through Github, using as much as possible tools like Transifex to facilitate participation, and providing guidelines for contributors as part of the project. Of course, this project cannot be realized without your support. We therefore come to you to inquire about your willingness to accompany and support this project. We would love to hear your feedback on our proposal. Best regards, Mariángela -- María Ángela Petrizzo Páez [image: https://] [image: https://]about.me/petrizzo <https://about.me/petrizzo?promo=email_sig&utm_source=product&utm_medium=ema…> Descárgate Redes para la Comprensión de la Política <http://www.elperroylarana.gob.ve/redes-para-la-comprension-de-la-politica/> *A quienes conservan la esperanza que no es lo último que se pierde, sino lo primero que se siembra y, por tanto, lo más radical.* El único modo de vencer el secuestro del conocimiento es comprender sus razones. La manera de revertirlo, es hacernos hackers de los secuestros cotidianos a cambio de no morir sin saber lo que somos ¡Piensa para vivir, actúa para hackear! Cada día, una acción procomún a la vez. *“Tengo horror de aquellos cuyas palabras van más allá que sus actos”* *Albert Camus* *“El poder, lejos de estorbar al saber, lo produce.” - **Michael Foucault* Usuario Linux # 498889 Miembro Red de Politólogas - #NoSinMujeres <http://www.nosinmujeres.com/> https://hotelescuela.academia.edu/MariangelaPetrizzoPaez http://orcid.org/0000-0001-9483-4185 PEII - Nivel B

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Invitation to lead a virtual sprint at SciPy US 2021
by Juan Nunez-Iglesias April 29, 2021

April 29, 2021

Hi all, I myself have come around to Gaël's idea that mature projects like scikit-learn are not the best place for newcomers to contribute. However, since the scikit-learn team has run a lot of remote, beginner friendly sprints in the past, there are clearly exceptions! Additionally, I suspect many people on this list have smaller projects that would make for great sprint topics. So, I would like to invite scikit-learners to submit sprint ideas for SciPy US 2021 here: https://forms.gle/w59mWNcA6JP9YA9z7 The sprint dates are July 17-18, and the sprint times are 9am-5pm US Central time. Please feel free to contact me if you have any questions about this. I'm happy to offer guidance on running a remote sprint for those that have suitable projects but have never run their own sprints before. (Though probably Reshama and Andy are the real pros here! 😂) Thank you, Juan.

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Re: [scikit-learn] scikit-learn Digest, Vol 61, Issue 12
by betsey_gogo April 29, 2021

April 29, 2021

INPUT import seaborn as sns iris = sns.load_dataset('iris') OUTPUT OSError Traceback (most recent call last) <ipython-input-1-842ca3e1f505> in <module> ----> 1 import seaborn as sns 2 iris = sns.load_dataset('iris') D:\Anaconda\lib\site-packages\seaborn\__init__.py in <module> 1 # Import seaborn objects ----> 2 from .rcmod import * # noqa: F401,F403 3 from .utils import * # noqa: F401,F403 4 from .palettes import * # noqa: F401,F403 5 from .relational import * # noqa: F401,F403 D:\Anaconda\lib\site-packages\seaborn\rcmod.py in <module> 3 import functools 4 from distutils.version import LooseVersion ----> 5 import matplotlib as mpl 6 from cycler import cycler 7 from . import palettes ~\AppData\Roaming\Python\Python38\site-packages\matplotlib\__init__.py in <module> 136 # cbook must import matplotlib only within function 137 # definitions, so it is safe to import from it here. --> 138 from . import cbook, rcsetup 139 from matplotlib.cbook import ( 140 MatplotlibDeprecationWarning, dedent, get_label, sanitize_sequence) ~\AppData\Roaming\Python\Python38\site-packages\matplotlib\cbook\__init__.py in <module> 30 from weakref import WeakMethod 31 ---> 32 import numpy as np 33 34 import matplotlib ~\AppData\Roaming\Python\Python38\site-packages\numpy\__init__.py in <module> 138 139 # Allow distributors to run custom init code --> 140 from . import _distributor_init 141 142 from . import core ~\AppData\Roaming\Python\Python38\site-packages\numpy\_distributor_init.py in <module> 24 # NOTE: would it change behavior to load ALL 25 # DLLs at this path vs. the name restriction? ---> 26 WinDLL(os.path.abspath(filename)) 27 DLL_filenames.append(filename) 28 if len(DLL_filenames) > 1: D:\Anaconda\lib\ctypes\__init__.py in __init__(self, name, mode, handle, use_errno, use_last_error, winmode) 379 380 if handle is None: --> 381 self._handle = _dlopen(self._name, mode) 382 else: 383 self._handle = handle OSError: [WinError 193] %1 is not a valid Win32 application

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[ANN] scikit-learn 0.24.2 is online!
by Guillaume Lemaître April 28, 2021

April 28, 2021

scikit-learn 0.24.2 is out on pypi.org and conda-forge! This is a small maintenance release that fixes a couple of regressions: https://scikit-learn.org/stable/whats_new/v0.24.html#version-0-24-2 You can upgrade with pip as usual: pip install -U scikit-learn The conda-forge builds will be available shortly, which you can then install using: conda install -c conda-forge scikit-learn Thanks again to all the contributors and let's work towards version 1.0! On behalf of the scikit-learn maintainer team. -- Guillaume Lemaitre Scikit-learn @ Inria Foundation https://glemaitre.github.io/

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scikit problems
by betsey_gogo April 26, 2021

April 26, 2021

I am getting frustrated. I am unable to run any scikit learning code because of an OS error OSError: [WinError 193] %1 is not a valid Win32 application I have tried 64 bit and 32 bit Anaconda installations to no avail. I have searched for help on the web. Others have seen this issue but the solutions are at best unclear. I don't know if I have an incorrect path variable of something more serious. Would you help? Orest Gogosha "GOGO"

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Efficient forward stepwise regression
by Matt Schoenbauer April 26, 2021

April 26, 2021

Hello sklearn developers, I'd like to implement a forward stepwise regression algorithm using the efficient procedure described in the first problem here <http://stat.rutgers.edu/home/hxiao/stat588_2011/hw1.pdf>. It does not seem that such a model exists anywhere in Python. Would it be useful for me to write this model up for sklearn? If you're interested, here's a high-level view of how I think it would work: - The model would have sklearn.linear_model.LinearRegression as its base class. - The additional model parameters would include - An array of the indices (or column names) of the features in X1 - The Q and R matrices - The additional methods would include - An add_features() method that adds a specified number of features to the model. Updates all model parameters - A fit() method that requires a specification of the number of parameters to fit and optional sample weight. It calls the add_features method once on a model with no features. I would do this for OLS first, but supposedly it could be adapted for regularized models as well. How does this sound? Thanks, Matt S.

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Monthly meeting April 26th 2021
by Chiara Marmo April 21, 2021

April 21, 2021

Dear list, The scikit-learn monthly meeting will take place on Monday April 26th at 1PM UTC: <https://www.timeanddate.com/worldclock/meetingdetails.html?year=2021&month=…> <https://www.timeanddate.com/worldclock/meetingdetails.html?year=2021&month=…> https://www.timeanddate.com/worldclock/meetingdetails.html?year=2021&month=… <https://www.google.com/url?q=https://www.timeanddate.com/worldclock/meeting…> <https://www.google.com/url?q=https://www.timeanddate.com/worldclock/meeting…> While these meetings are mainly for core-devs to discuss the current topics, non core-devs and other project maintainers are welcome. 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/k4gBAPkZR-GpQSOd80pFpQ#Contributors>" section, of the public pad: <https://hackmd.io/qtKt7pTNSXanU-MJOIMxbw> https://hackmd.io/k4gBAPkZR-GpQSOd80pFpQ Best Chiara

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ANN: scikit-learn-extra 0.2.0 released
by Timothee Mathieu April 17, 2021

April 17, 2021

Hello, We're happy to announce the 0.2.0 version of scikit-learn-extra. scikit-learn-extra is a Python module for machine learning that extends scikit-learn. It includes algorithms that are useful but do not satisfy the scikit-learn inclusion criteria. This new release includes in particular new clustering and robust algorithms. This release should be fully compatible with scikit-learn 0.23 The full changelog can be found here: [ https://scikit-learn-extra.readthedocs.io/en/latest/changelog.html#version-… | https://scikit-learn-extra.readthedocs.io/en/latest/changelog.html#version-… ] The new release of scikit-learn-extra is available via pip and conda. For more information, please visit the documentation: [ https://scikit-learn-extra.readthedocs.io/en/stable/ | https://scikit-learn-extra.readthedocs.io/en/stable/ ] Best regards, Timothée, on behalf of the scikit-learn-extra team.

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