Mailman 3 August 2021 - scikit-learn

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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Regarding negative value of sklearn.metrics.r2_score and sklearn.metrics.explained_variance_score
by Samir K Mahajan Aug. 14, 2021

Aug. 14, 2021

Dear All, I am amazed to find negative values of sklearn.metrics.r2_score and sklearn.metrics.explained_variance_score in a model ( cross validation of OLS regression model) However, what amuses me more is seeing you justifying negative 'sklearn.metrics.r2_score ' in your documentation. This does not make sense to me . Please justify to me how squared values are negative. Regards, Samir K Mahajan.

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random forests and multil-class probability
by Sole Galli Aug. 14, 2021

Aug. 14, 2021

Hello community, Do I understand correctly that Random Forests are trained as a 1 vs rest when the target has more than 2 classes? Say the target takes values 0, 1 and 2, then the model would train 3 estimators 1 per class under the hood?. The predict_proba output is an array with 3 columns, containing the probability of each class. If it is 1 vs rest. am I correct to assume that the sum of the probabilities for the 3 classes should not necessarily add up to 1? are they normalized? how is it done so that they do add up to 1? Thank you Sole

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scikit-learn for Apple Silicon M1 Macs
by Uroš Poček Aug. 2, 2021

Aug. 2, 2021

Hello, I am a student and ML programmer and I have been using scikit-learn library for python for a few years now on my PC, but recently I switched to M1 iMac and when I tried to transfer my projects and pip install used libraries in them I ran in bunch of issues. Long story short I was able to successfully install all ML libraries on my new Mac(tensorflow, numpy, matplotlib, pandas, torch, …) except scikit-learn (sklearn)! When can we expect to see version of this library that can be installed using pip on M1 Macs and that can be used without any issues? Thank you all in advance. Uros Pocek

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