Mailman 3 December 2020 - scikit-learn

[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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Question RE: skLearn Logistic Regression
by The Helmbolds March 6, 2021

March 6, 2021

I have a case with binary results and 1-D features, like: X = np.array(-3,-2,-1,0,1,2,3,) and y = np.array(0, 0, 0, 1, 1, 1, 1) only longer arrays (about 180 entries in each array) of this general type. So this should be the "simplest" case. Altho I've tried several variations of the Logistic input formats, in LogisticRegression.fit(X, y) they keep being rejected with the most common error message being Missing argument y I assure you I do indeed have an array "y" that is passed to "fit" So----What do I have to do to get Logistic Regression to accept 1-D features?

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Comparing Scikit and Xlstat for PCA analysis
by Mahmood Naderan Jan. 5, 2021

Jan. 5, 2021

Hi I have a test csv file and I have written a code to show the PCA for that. I also use another tool in Excel (XLSTAT) to compare the results. The XLSTAT automatically calculates the number of features, however, based on my understanding, I have to specify how many components are needed using the scikit package. For example, while XLSTAT shows 5 features: Factor scores: F1 F2 F3 F4 F5 A1 -1.293 -0.663 -0.462 -0.713 0.010 A2 -0.297 0.293 -1.429 0.397 0.056 A3 2.328 0.069 0.987 -0.108 0.062 A4 -0.556 -2.273 0.538 0.344 -0.032 A5 1.823 0.775 -0.597 -0.052 -0.085 A6 -2.005 1.799 0.963 0.133 -0.011 In the following code, I specified 2 components: x = StandardScaler().fit_transform(x) pca = PCA(n_components=2) principalComponents = pca.fit_transform(x) print( principalComponents ) [[-1.29292842 0.66325508] [-0.29706395 -0.29346337] [ 2.32751305 -0.06850045] [-0.5558091 2.27288988] [ 1.82312052 -0.77527304] [-2.0048321 -1.7989081 ]] As you can see, the first column in XLSTAT and scikit are the same. However, the second columns are negated. For example, considering F1 and F2, we see XLSTAT => -1.293 -0.663 scikit => [-1.29292842 0.66325508] So, my questions are 1) Isn't there any way to use scikit for an unknown number of principal components? So that I can query the number of principal components and use a scree plot then. 2) Considering the F1 and F2 as a XY scatter point, I want to know why the value of Y in XLSTAT and scikit are opposite? The code which I write is available at https://pastebin.com/ghJQ6L4C Any idea? Regards, Mahmood

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Interpreting results of random forest classifier
by DAVID cofield Dec. 28, 2020

Dec. 28, 2020

Could someone explain what the probability values provided by the random forest classifier represents? When I run the classifier with two classes, I get prediction values and associated to these prediction values are probabilities. As I understand it now the 0 probability is probability that the prediction is wrong, and the 1 probability is the probability that the prediction is correct. One thing I do not understand is why the probability ranges do not go from 0 to 100; they go from 0 to 49 for 0 probability and 49-100 for 1 probability. How do I interpret the probabilities? Sent from Mail<https://go.microsoft.com/fwlink/?LinkId=550986> for Windows 10

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Monthly meeting January 4th 2021
by Chiara Marmo Dec. 28, 2020

Dec. 28, 2020

Dear list, The first 2021 scikit-learn monthly meeting will take place on Monday January 4th at 8PM UTC: https://www.timeanddate.com/worldclock/meetingdetails.html?year=2021&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/qtKt7pTNSXanU-MJOIMxbw#Contributors>" section, of the public pad: https://hackmd.io/qtKt7pTNSXanU-MJOIMxbw Best Chiara

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ANN scikit-learn 0.24.0 release
by Guillaume Lemaître Dec. 23, 2020

Dec. 23, 2020

We're happy to announce the 0.24.0 release and already out on PyPI and conda-forge. You can read the release highlights under https://scikit-learn.org/stable/auto_examples/release_highlights/plot_relea… and the long version of the change log under https://scikit-learn.org/stable/whats_new/v0.24.html#version-0-24-0 New major features include: Highlights include successive halving, categorical support for GBRT, SelfTrainingClassifier, SequentialFeatureSelector and much more! This version supports Python versions 3.6 to 3.9. You can give it a go using `pip install -U scikit-learn` or `conda install -c conda-forge scikit-learn`. A big thanks to all contributors for making this release possible. Regards, On the behalf of the scikit-learn maintainer team. -- Guillaume Lemaitre Scikit-learn @ Inria Foundation https://glemaitre.github.io/

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Daily failure: Run failed: Wheel builder - master (1e53ae2)
by Adrin Dec. 17, 2020

Dec. 17, 2020

Hi, I keep getting this email every night, sending it here to make sure we're aware of it. Cheers, Adrin ---------- Forwarded message --------- From: Adrin Jalali <notifications(a)github.com> Date: Thu., Dec. 17, 2020, 05:21 Subject: [adrinjalali/scikit-learn] Run failed: Wheel builder - master (1e53ae2) To: adrinjalali/scikit-learn <scikit-learn(a)noreply.github.com> Cc: Ci activity <ci_activity(a)noreply.github.com> [image: GitHub] [adrinjalali/scikit-learn] Wheel builder workflow run Wheel builder: Some jobs were not successful View workflow run <https://github.com/adrinjalali/scikit-learn/actions/runs/427220167> [image: Check build trigger] *Wheel builder* / Check build trigger Succeeded in 17 seconds [image: Build wheel for cp36-win32] *Wheel builder* / Build wheel for cp36-win32 Succeeded in 21 minutes [image: Build wheel for cp36-win_amd64] *Wheel builder* / Build wheel for cp36-win_amd64 Succeeded in 20 minutes and 3 seconds [image: Build wheel for cp37-win32] *Wheel builder* / Build wheel for cp37-win32 Succeeded in 19 minutes and 20 seconds [image: Build wheel for cp37-win_amd64] *Wheel builder* / Build wheel for cp37-win_amd64 Succeeded in 22 minutes and 28 seconds [image: Build wheel for cp38-win32] *Wheel builder* / Build wheel for cp38-win32 Succeeded in 19 minutes and 39 seconds [image: Build wheel for cp38-win_amd64] *Wheel builder* / Build wheel for cp38-win_amd64 Succeeded in 21 minutes and 21 seconds [image: Build wheel for cp39-win32] *Wheel builder* / Build wheel for cp39-win32 Succeeded in 20 minutes and 37 seconds [image: Build wheel for cp39-win_amd64] *Wheel builder* / Build wheel for cp39-win_amd64 Succeeded in 24 minutes and 7 seconds [image: Build wheel for cp36-manylinux_i686] *Wheel builder* / Build wheel for cp36-manylinux_i686 Succeeded in 17 minutes and 50 seconds View all 23 job statuses <https://github.com/adrinjalali/scikit-learn/actions/runs/427220167> — You are receiving this because this workflow ran on your branch. Manage your GitHub Actions notifications <https://github.com/settings/notifications> GitHub, Inc. ・88 Colin P Kelly Jr Street ・San Francisco, CA 94107

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Using text labels in dendrogram
by Mahmood Naderan Dec. 15, 2020

Dec. 15, 2020

Hi I use the following code to create a dendrogram from a set of x-y points import matplotlib.pyplot as plt import numpy as np from scipy.cluster.hierarchy import dendrogram, linkage a = np.array([ [5.840,-2.339], [6.320,-2.665], [-1.698,-0.084], ],) linked = linkage(a, 'single') labelList = range(1, 69) dendrogram(linked, orientation='top', labels=labelList, distance_sort='descending', show_leaf_counts=True) plt.show() This code automatically assigns labels for the points and the result is not sorted. For example, the x-axis labels are 2 1 3. I want to assign a text for each point. Then no matter where the point goes, I can see the text that I have assigned. For example, I want to see PDD, XDD, BDD. How can I create a list of text labels and bind that to the array a? Regards, Mahmood

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Drawing contours in KMeans
by Mahmood Naderan Dec. 10, 2020

Dec. 10, 2020

Hi I use the following code to highlight the cluster centers with some red dots. kmeans = KMeans(n_clusters=6, init='k-means++', max_iter=100, n_init=10, random_state=0) pred_y = kmeans.fit_predict(a) plt.scatter(a[:,0], a[:,1]) plt.scatter(kmeans.cluster_centers_[:, 0], kmeans.cluster_centers_[:, 1], s=100, c='red') plt.show() I would like to know if it is possible to draw contours over the clusters. Is there any way for that? Please let me know if there is a function or option in KMeans. Regards, Mahmood

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Changes in Travis billing
by Gael Varoquaux Dec. 8, 2020

Dec. 8, 2020

Travis is changing it's billing strategy: https://blog.travis-ci.com/2020-11-02-travis-ci-new-billing Open repositories are getting a free initial set of credit. They invite open source projects to contact them to benefit from a more liberal policy. I suggest that we do the latter, as I fear that we might run out of credits, and I am quite convinced that we could benefit from the liberal policy. Cheers, Gaël -- Gael Varoquaux Research Director, INRIA Visiting professor, McGill http://gael-varoquaux.info http://twitter.com/GaelVaroquaux

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