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Subject: CVS commit: pkgsrc/math/py-scikit-learn
From: Adam Ciarcinski
Date: 2019-06-17 17:01:45
Message id: 20190617150145.CC61BFBF4@cvs.NetBSD.org
Log Message:
py-scikit-learn: 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 un-instanciated 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 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.
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 cross-validation with sparse inputs
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