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StratifiedGroupKFold — scikit-learn 1.5.0 docum...
1 , 1 , 1 , 1 , 1 , 1 , 0 , 0 , 0 , 0 , 0...Train: index=[ 0 1 2 3 7 8 9 10 11 15 16] group=[1 1 2 2 4 5 5 5 5...scikit-learn.org/stable/modules/generated/sklearn.model_selection.StratifiedGroupKFold.html -
Version 1.2 — scikit-learn 1.6.dev0 documentation
is deprecated in 1.2.1 and will be removed in 1.5. Instead, import...raised in version 1.2 when min_sample_split=1 . #25744 by Jérémie...scikit-learn.org/dev/whats_new/v1.2.html -
RobustScaler — scikit-learn 1.5.0 documentation
[[ 1. , - 2. , 2. ], ... [ - 2. , 1. , 3. ], ... [ 4. , 1. ,..., -2. , 0. ], [-1. , 0. , 0.4], [ 1. , 0. , -1.6]]) fit ( X ,...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.RobustScaler.html -
HDBSCAN — scikit-learn 1.5.0 documentation
-1, ..., -1, -1, -1]) dbscan_clustering (...version 1.4: The 'kdtree' option was deprecated in version 1.4, and...scikit-learn.org/stable/modules/generated/sklearn.cluster.HDBSCAN.html -
OutputCodeClassifier — scikit-learn 1.5.0 docum...
means 1 unless in a joblib.parallel_backend context. -1 means...( estimator , * , code_size = 1.5 , random_state = None , n_jobs...scikit-learn.org/stable/modules/generated/sklearn.multiclass.OutputCodeClassifier.html -
LassoLarsIC — scikit-learn 1.5.0 documentation
[ - 1 , 1 ], [ 0 , 0 ], [ 1 , 1 ], [ 2 , 2 ]] >>>...fit_intercept . Added in version 1.1. Attributes : coef_ array-like...scikit-learn.org/stable/modules/generated/sklearn.linear_model.LassoLarsIC.html -
Version 1.4 — scikit-learn 1.6.dev0 documentation
Version 1.4.1 # February 2024 Metadata Routing...deprecated in version 1.4 and will be removed in version 1.6. Use the default...scikit-learn.org/dev/whats_new/v1.4.html -
make_column_selector — scikit-learn 1.5.0 docum...
1. , 0. , 0. ], [-1.50755672, 1. , 0. , 0. ], [-0.30151134,...[-0.30151134, 0. , 1. , 0. ], [ 0.90453403, 0. , 0. , 1. ]]) __call__...scikit-learn.org/stable/modules/generated/sklearn.compose.make_column_selector.html -
Unsupervised learning: seeking representations ...
array ([[ 1 , 1 , 1 ], [ 0.5 , 2 , 1 ], [ 1.5 , 1 , 2 ]]) # Mixing...k_means . labels_ [:: 10 ]) [1 1 1 1 1 2 0 0 0 0 2 2 2 2 2] >>> print...scikit-learn.org/stable/tutorial/statistical_inference/unsupervised_learning.html -
shuffle — scikit-learn 1.5.0 documentation
1.], [1., 0.]]) >>> y array([2, 1, 0]) >>> shuffle...>>> X = np . array ([[ 1. , 0. ], [ 2. , 1. ], [ 0. , 0. ]]) >>>...scikit-learn.org/stable/modules/generated/sklearn.utils.shuffle.html