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math/pyscikitlearn,
Machine learning algorithms for Python
Branch: CURRENT,
Version: 0.22.1nb1,
Package name: py38scikitlearn0.22.1nb1,
Maintainer: pkgsrcusersscikitlearn is a Python module integrating classic machine learning
algorithms in the tightlyknit 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: machinelearning as a versatile tool for science and
engineering.
Required to run:[
math/lapack] [
math/blas] [
devel/pysetuptools] [
math/pyscipy] [
math/pynumpy] [
devel/pycython] [
lang/gcc7] [
lang/python37] [
devel/pyjoblib]
Required to build:[
pkgtools/cwrappers]
Master sites:
SHA1: 84f75ff3e6ed92a71d8f241ba520de57e97475f7
RMD160: cee5fd1ff80ec39e9b229b26cf22a25a3664a36d
Filesize: 6780.254 KB
Version history: (Expand)
 (20210409) Updated to version: py38scikitlearn0.22.1nb1
 (20201013) Updated to version: py37scikitlearn0.22.1nb1
 (20200211) Updated to version: py37scikitlearn0.22.1
 (20190625) Updated to version: py37scikitlearn0.21.2
 (20181002) Updated to version: py27scikitlearn0.20.0
 (20180806) Updated to version: py27scikitlearn0.19.2
CVS history: (Expand)
20210420 23:48:14 by Dr. Thomas Orgis  Files touched by this commit (1) 
Log message:
math/pyscikitlearn: drop explicit BLAS dependency
This adds nothing on the normal dependency to numpy.

20210409 16:41:35 by Tobias Nygren  Files touched by this commit (14) 
Log message:
revert wrong fix for pyscipy python 3.6 deprecation, fix properly

20201012 23:52:05 by Jason Bacon  Files touched by this commit (87)  
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
implementation.
Details:
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

20200527 21:37:44 by Thomas Klausner  Files touched by this commit (60) 
Log message:
*: reset MAINTAINER for fhajny on his request

20200211 17:06:45 by Min Sik Kim  Files touched by this commit (4)  
Log message:
math/pyscikitlearn: Update to 0.22.1
Highlights:
 New plotting API
 Stacking Classifier and Regressor
 Permutationbased 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 scikitlearn compatibility of an estimator
 ROC AUC now supports multiclass classification

20200126 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 sideeffect of migrating the homepages, pkglint also fixed a few
indentations in unrelated lines. These and the new homepages have been
checked manually.

20190617 17:01:45 by Adam Ciarcinski  Files touched by this commit (5)  
Log message:
pyscikitlearn: updated to 0.21.2
Version 0.21.2
Changelog
sklearn.decomposition
Fix Fixed a bug in cross_decomposition.CCA improving numerical stability when Y \
is close to zero.
sklearn.metrics
Fix Fixed a bug in metrics.pairwise.euclidean_distances where a part of the \
distance matrix was left uninstanciated for suffiently large float32 datasets \
(regression introduced in 0.21).
sklearn.preprocessing
Fix Fixed a bug in preprocessing.OneHotEncoder where the new drop parameter was \
not reflected in get_feature_names.
sklearn.utils.sparsefuncs
Fix Fixed a bug where min_max_axis would fail on 32bit systems for certain \
large inputs. This affects preprocessing.MaxAbsScaler, preprocessing.normalize \
and preprocessing.LabelBinarizer.
Version 0.21.1
This is a bugfix release to primarily resolve some packaging issues in version \
0.21.0. It also includes minor documentation improvements and some bug fixes.
Changelog
sklearn.metrics
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.
sklearn.neighbors
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 crossvalidation with sparse inputs

20181215 22:12:25 by Thomas Klausner  Files touched by this commit (67)  
Log message:
*: update email for fhajny
