./math/py-scikit-learn, Machine learning algorithms for Python

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Branch: CURRENT, Version: 0.22.1nb1, Package name: py38-scikit-learn-0.22.1nb1, Maintainer: pkgsrc-users

scikit-learn is a Python module integrating classic machine learning
algorithms in the tightly-knit scientific Python world (numpy, scipy,
matplotlib). It aims to provide simple and efficient solutions to
learning problems, accessible to everybody and reusable in various
contexts: machine-learning as a versatile tool for science and

Required to run:
[math/lapack] [math/blas] [devel/py-setuptools] [math/py-scipy] [math/py-numpy] [devel/py-cython] [lang/gcc7] [lang/python37] [devel/py-joblib]

Required to build:

Master sites:

SHA1: 84f75ff3e6ed92a71d8f241ba520de57e97475f7
RMD160: cee5fd1ff80ec39e9b229b26cf22a25a3664a36d
Filesize: 6780.254 KB

Version history: (Expand)

CVS history: (Expand)

   2021-04-20 23:48:14 by Dr. Thomas Orgis | Files touched by this commit (1)
Log message:
math/py-scikit-learn: drop explicit BLAS dependency

This adds nothing on the normal dependency to numpy.
   2021-04-09 16:41:35 by Tobias Nygren | Files touched by this commit (14)
Log message:
revert wrong fix for py-scipy python 3.6 deprecation, fix properly
   2020-10-12 23:52:05 by Jason Bacon | Files touched by this commit (87) | Package updated
Log message:
math/blas, math/lapack: Install interchangeable BLAS system

Install the new interchangeable BLAS system created by Thomas Orgis,
currently supporting Netlib BLAS/LAPACK, OpenBLAS, cblas, lapacke, and
Apple's Accelerate.framework.  This system allows the user to select any
BLAS implementation without modifying packages or using package options, by
setting PKGSRC_BLAS_TYPES in mk.conf. See mk/blas.buildlink3.mk for details.

This commit should not alter behavior of existing packages as the system
defaults to Netlib BLAS/LAPACK, which until now has been the only supported


Add new mk/blas.buildlink3.mk for inclusion in dependent packages
Install compatible Netlib math/blas and math/lapack packages
Update math/blas and math/lapack MAINTAINER approved by adam@
OpenBLAS, cblas, and lapacke will follow in separate commits
Update direct dependents to use mk/blas.buildlink3.mk
Perform recursive revbump
   2020-05-27 21:37:44 by Thomas Klausner | Files touched by this commit (60)
Log message:
*: reset MAINTAINER for fhajny on his request
   2020-02-11 17:06:45 by Min Sik Kim | Files touched by this commit (4) | Package updated
Log message:
math/py-scikit-learn: Update to 0.22.1


- New plotting API
- Stacking Classifier and Regressor
- Permutation-based feature importance
- Native support for missing values for gradient boosting
- Precomputed sparse nearest neighbors graph
- KNN Based Imputation
- Tree pruning
- Retrieve dataframes from OpenML
- Checking scikit-learn compatibility of an estimator
- ROC AUC now supports multiclass classification
   2020-01-26 18:32:28 by Roland Illig | Files touched by this commit (981)
Log message:
all: migrate homepages from http to https

pkglint -r --network --only "migrate"

As a side-effect of migrating the homepages, pkglint also fixed a few
indentations in unrelated lines. These and the new homepages have been
checked manually.
   2019-06-17 17:01:45 by Adam Ciarcinski | Files touched by this commit (5) | Package updated
Log message:
py-scikit-learn: updated to 0.21.2

Version 0.21.2
Fix Fixed a bug in cross_decomposition.CCA improving numerical stability when Y \ 
is close to zero.

Fix Fixed a bug in metrics.pairwise.euclidean_distances where a part of the \ 
distance matrix was left un-instanciated for suffiently large float32 datasets \ 
(regression introduced in 0.21).

Fix Fixed a bug in preprocessing.OneHotEncoder where the new drop parameter was \ 
not reflected in get_feature_names.

Fix Fixed a bug where min_max_axis would fail on 32-bit systems for certain \ 
large inputs. This affects preprocessing.MaxAbsScaler, preprocessing.normalize \ 
and preprocessing.LabelBinarizer.

Version 0.21.1
This is a bug-fix release to primarily resolve some packaging issues in version \ 
0.21.0. It also includes minor documentation improvements and some bug fixes.

Fix Fixed a bug in metrics.pairwise_distances where it would raise \ 
AttributeError for boolean metrics when X had a boolean dtype and Y == None.
Fix Fixed two bugs in metrics.pairwise_distances when n_jobs > 1. First it \ 
used to return a distance matrix with same dtype as input, even for integer \ 
dtype. Then the diagonal was not zeros for euclidean metric when Y is X.

Fix Fixed a bug in neighbors.KernelDensity which could not be restored from a \ 
pickle if sample_weight had been used.

Version 0.21.0
Changed models
The following estimators and functions, when fit with the same data and \ 
parameters, may produce different models from the previous version. This often \ 
occurs due to changes in the modelling logic (bug fixes or enhancements), or in \ 
random sampling procedures.
discriminant_analysis.LinearDiscriminantAnalysis for multiclass classification. Fix
discriminant_analysis.LinearDiscriminantAnalysis with ‘eigen’ solver. Fix
linear_model.BayesianRidge Fix
Decision trees and derived ensembles when both max_depth and max_leaf_nodes are \ 
set. Fix
linear_model.LogisticRegression and linear_model.LogisticRegressionCV with \ 
‘saga’ solver. Fix
ensemble.GradientBoostingClassifier Fix
sklearn.feature_extraction.text.HashingVectorizer, \ 
sklearn.feature_extraction.text.TfidfVectorizer, and \ 
sklearn.feature_extraction.text.CountVectorizer Fix
neural_network.MLPClassifier Fix
svm.SVC.decision_function and multiclass.OneVsOneClassifier.decision_function. Fix
linear_model.SGDClassifier and any derived classifiers. Fix
Any model using the linear_model.sag.sag_solver function with a 0 seed, \ 
including linear_model.LogisticRegression, linear_model.LogisticRegressionCV, \ 
linear_model.Ridge, and linear_model.RidgeCV with ‘sag’ solver. Fix
linear_model.RidgeCV when using generalized cross-validation with sparse inputs
   2018-12-15 22:12:25 by Thomas Klausner | Files touched by this commit (67) | Package updated
Log message:
*: update email for fhajny