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here is the log from the commit of package python-scikit-learn for
openSUSE:Factory checked in at 2022-02-03 23:16:13
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Comparing /work/SRC/openSUSE:Factory/python-scikit-learn (Old)
and /work/SRC/openSUSE:Factory/.python-scikit-learn.new.1898 (New)
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Package is "python-scikit-learn"
Thu Feb 3 23:16:13 2022 rev:16 rq:950579 version:1.0.2
Changes:
--------
--- /work/SRC/openSUSE:Factory/python-scikit-learn/python-scikit-learn.changes
2021-06-11 22:30:37.806125639 +0200
+++
/work/SRC/openSUSE:Factory/.python-scikit-learn.new.1898/python-scikit-learn.changes
2022-02-03 23:16:46.340495692 +0100
@@ -1,0 +2,31 @@
+Wed Feb 2 02:07:05 UTC 2022 - Steve Kowalik <[email protected]>
+
+- Update to 1.0.2:
+ * Fixed an infinite loop in cluster.SpectralClustering by moving an
iteration counter from try to except. #21271 by Tyler Martin.
+ * datasets.fetch_openml is now thread safe. Data is first downloaded to a
temporary subfolder and then renamed. #21833 by Siavash Rezazadeh.
+ * Fixed the constraint on the objective function of
decomposition.DictionaryLearning, decomposition.MiniBatchDictionaryLearning,
decomposition.SparsePCA and decomposition.MiniBatchSparsePCA to be convex and
match the referenced article. #19210 by J??r??mie du Boisberranger.
+ * ensemble.RandomForestClassifier, ensemble.RandomForestRegressor,
ensemble.ExtraTreesClassifier, ensemble.ExtraTreesRegressor, and
ensemble.RandomTreesEmbedding now raise a ValueError when bootstrap=False and
max_samples is not None. #21295 Haoyin Xu.
+ * Solve a bug in ensemble.GradientBoostingClassifier where the exponential
loss was computing the positive gradient instead of the negative one. #22050 by
Guillaume Lemaitre.
+ * Fixed feature_selection.SelectFromModel by improving support for base
estimators that do not set feature_names_in_. #21991 by Thomas Fan.
+ * Fix a bug in linear_model.RidgeClassifierCV where the method predict was
performing an argmax on the scores obtained from decision_function instead of
returning the multilabel indicator matrix. #19869 by Guillaume Lemaitre.
+ * linear_model.LassoLarsIC now correctly computes AIC and BIC. An error is
now raised when n_features > n_samples and when the noise variance is not
provided. #21481 by Guillaume Lemaitre and Andr??s Babino.
+ * Fixed an unnecessary error when fitting manifold.Isomap with a precomputed
dense distance matrix where the neighbors graph has multiple disconnected
components. #21915 by Tom Dupre la Tour.
+ * All sklearn.metrics.DistanceMetric subclasses now correctly support
read-only buffer attributes. This fixes a regression introduced in 1.0.0 with
respect to 0.24.2. #21694 by Julien Jerphanion.
+ * neighbors.KDTree and neighbors.BallTree correctly supports read-only
buffer attributes. #21845 by Thomas Fan.
+ * Fixes compatibility bug with NumPy 1.22 in preprocessing.OneHotEncoder.
#21517 by Thomas Fan.
+ * Prevents tree.plot_tree from drawing out of the boundary of the figure.
#21917 by Thomas Fan.
+ * Support loading pickles of decision tree models when the pickle has been
generated on a platform with a different bitness. A typical example is to train
and pickle the model on 64 bit machine and load the model on a 32 bit machine
for prediction. #21552 by Lo??c Est??ve.
+ * Non-fit methods in the following classes do not raise a UserWarning when
fitted on DataFrames with valid feature names: covariance.EllipticEnvelope,
ensemble.IsolationForest, ensemble.AdaBoostClassifier,
neighbors.KNeighborsClassifier, neighbors.KNeighborsRegressor,
neighbors.RadiusNeighborsClassifier, neighbors.RadiusNeighborsRegressor. #21199
by Thomas Fan.
+ * Fixed calibration.CalibratedClassifierCV to take into account
sample_weight when computing the base estimator prediction when ensemble=False.
#20638 by Julien Bohn??.
+ * Fixed a bug in calibration.CalibratedClassifierCV with method="sigmoid"
that was ignoring the sample_weight when computing the the Bayesian priors.
#21179 by Guillaume Lemaitre.
+ * Compute y_std properly with multi-target in
sklearn.gaussian_process.GaussianProcessRegressor allowing proper normalization
in multi-target scene. #20761 by Patrick de C. T. R. Ferreira.
+ * Fixed a bug in feature_extraction.CountVectorizer and
feature_extraction.TfidfVectorizer by raising an error when ???min_idf??? or
???max_idf??? are floating-point numbers greater than 1. #20752 by Alek
Lefebvre.
+ * linear_model.LogisticRegression now raises a better error message when the
solver does not support sparse matrices with int64 indices. #21093 by Tom Dupre
la Tour.
+ * neighbors.KNeighborsClassifier, neighbors.KNeighborsRegressor,
neighbors.RadiusNeighborsClassifier, neighbors.RadiusNeighborsRegressor with
metric="precomputed" raises an error for bsr and dok sparse matrices in
methods: fit, kneighbors and radius_neighbors, due to handling of explicit
zeros in bsr and dok sparse graph formats. #21199 by Thomas Fan.
+ * pipeline.Pipeline.get_feature_names_out correctly passes feature names out
from one step of a pipeline to the next. #21351 by Thomas Fan.
+ * svm.SVC and svm.SVR check for an inconsistency in its internal
representation and raise an error instead of segfaulting. This fix also
resolves CVE-2020-28975. #21336 by Thomas Fan.
+ * manifold.TSNE now avoids numerical underflow issues during affinity matrix
computation.
+ * manifold.Isomap now connects disconnected components of the neighbors
graph along some minimum distance pairs, instead of changing every infinite
distances to zero.
+ * Many others, see full changelog at
https://scikit-learn.org/dev/whats_new/v1.0.html
+
+-------------------------------------------------------------------
Old:
----
scikit-learn-0.24.2.tar.gz
New:
----
scikit-learn-1.0.2.tar.gz
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Other differences:
------------------
++++++ python-scikit-learn.spec ++++++
--- /var/tmp/diff_new_pack.vA01Ah/_old 2022-02-03 23:16:47.140490231 +0100
+++ /var/tmp/diff_new_pack.vA01Ah/_new 2022-02-03 23:16:47.144490203 +0100
@@ -1,7 +1,7 @@
#
# spec file for package python-scikit-learn
#
-# Copyright (c) 2021 SUSE LLC
+# Copyright (c) 2022 SUSE LLC
#
# All modifications and additions to the file contributed by third parties
# remain the property of their copyright owners, unless otherwise agreed
@@ -16,13 +16,11 @@
#
-%{?!python_module:%define python_module() python-%{**} python3-%{**}}
+%{?!python_module:%define python_module() python3-%{**}}
%define skip_python2 1
-# SciPy 1.6.0 and NumPy 1.20 dropped Python 3.6 support.
-%define skip_python36 1
%bcond_with extratest
Name: python-scikit-learn
-Version: 0.24.2
+Version: 1.0.2
Release: 0
Summary: Python modules for machine learning and data mining
License: BSD-3-Clause
@@ -31,8 +29,8 @@
BuildRequires: %{python_module Cython >= 0.28.5}
BuildRequires: %{python_module devel}
BuildRequires: %{python_module joblib >= 0.11}
-BuildRequires: %{python_module numpy-devel >= 1.13.3}
-BuildRequires: %{python_module scipy >= 0.19.1}
+BuildRequires: %{python_module numpy-devel >= 1.14.6}
+BuildRequires: %{python_module scipy >= 1.1.0}
BuildRequires: %{python_module setuptools}
BuildRequires: %{python_module threadpoolctl >= 2.0.0}
BuildRequires: %{python_module xml}
@@ -42,8 +40,8 @@
BuildRequires: openblas-devel
BuildRequires: python-rpm-macros
Requires: python-joblib >= 0.11
-Requires: python-numpy >= 1.13.3
-Requires: python-scipy >= 0.19.1
+Requires: python-numpy >= 1.14.6
+Requires: python-scipy >= 1.0.0
Requires: python-threadpoolctl >= 2.0.0
Requires: python-xml
Provides: python-sklearn
++++++ scikit-learn-0.24.2.tar.gz -> scikit-learn-1.0.2.tar.gz ++++++
/work/SRC/openSUSE:Factory/python-scikit-learn/scikit-learn-0.24.2.tar.gz
/work/SRC/openSUSE:Factory/.python-scikit-learn.new.1898/scikit-learn-1.0.2.tar.gz
differ: char 5, line 1
