- 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 Jérémie 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 Andrés 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 Loïc Estève.
* 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 Bohné.
* 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