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2.8. Density Estimation — scikit-learn 1.7.2 do...
[ - 2 , - 1 ], [ - 3 , - 2 ], [ 1 , 1 ], [ 2 , 1 ], [ 3...the distribution of points. 2.8.2. Kernel Density Estimation #...scikit-learn.org/stable/modules/density.html -
make_hastie_10_2 — scikit-learn 1.7.2 documenta...
make_hastie_10_2 # sklearn.datasets. make_hastie_10_2 ( n_samples...make_hastie_10_2 >>> X , y = make_hastie_10_2 ( n_samples = 24000...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_hastie_10_2.html -
5.2. Permutation feature importance — scikit-le...
2.2. Relation to impurity-based importance...Ctrl + K GitHub Choose version 5.2. Permutation feature importance...scikit-learn.org/stable/modules/permutation_importance.html -
Version 1.2 — scikit-learn 1.7.2 documentation
2.2 # March 2023 Changelog # sklearn.base...GitHub Choose version Version 1.2 # For a short description of the...scikit-learn.org/stable/whats_new/v1.2.html -
2.5. Decomposing signals in components (matrix ...
o)}{2} ||H||_{\mathrm{Fro}} ^ 2) * n\_samples\] 2.5.7.2. NMF...2009 2.5.2. Kernel Principal Component Analysis (kPCA) # 2.5.2.1....scikit-learn.org/stable/modules/decomposition.html -
2.1. Gaussian mixture models — scikit-learn 1.7...
2.1.2. Variational Bayesian Gaussian...models using a finite mixture. 2.1.2.1. The Dirichlet Process # Here...scikit-learn.org/stable/modules/mixture.html -
StratifiedGroupKFold — scikit-learn 1.7.2 docum...
index=[ 0 1 2 3 15 16] group=[1 1 2 2 8 8] Fold 2: Train: index=[...index=[ 0 1 2 3 7 8 9 10 11 15 16] group=[1 1 2 2 4 5 5 5 5 8...scikit-learn.org/stable/modules/generated/sklearn.model_selection.StratifiedGroupKFold.html -
shuffle — scikit-learn 1.7.2 documentation
2)> >>> X_sparse . toarray () array([[0., 0.], [2., 1.],...y array([2, 1, 0]) >>> shuffle ( y , n_samples = 2 , random_state...scikit-learn.org/stable/modules/generated/sklearn.utils.shuffle.html -
PoissonRegressor — scikit-learn 1.7.2 documenta...
determination R^2. R^2 uses squared error and D^2 uses the deviance...PoissonRegressor () >>> X = [[ 1 , 2 ], [ 2 , 3 ], [ 3 , 4 ], [ 4 , 3...scikit-learn.org/stable/modules/generated/sklearn.linear_model.PoissonRegressor.html -
PLSRegression — scikit-learn 1.7.2 documentation
[ 2. , 2. , 2. ], [ 2. , 5. , 4. ]] >>> y =...= [[ 0.1 , - 0.2 ], [ 0.9 , 1.1 ], [ 6.2 , 5.9 ], [ 11.9 , 12.3...scikit-learn.org/stable/modules/generated/sklearn.cross_decomposition.PLSRegression.html