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Fitting an Elastic Net with a precomputed Gram ...
-1.67451144e+02], [-4.48938813e+02, 1.00768662e+05, 1.19112072e+02,...-3.53959628e+02, -1.67451144e+02], [-4.48938813e+02, 1.00768662e+05, 1.19112072e+02,...scikit-learn.org/stable/auto_examples/linear_model/plot_elastic_net_precomputed_gram_matrix_with_... -
sklearn.metrics — scikit-learn 1.8.0 docu...
Score functions, performance metrics, pairwise metrics and distance computations. User guide. See the Metrics and scoring: quantifying the quality of predictions and Pairwise metrics, Affinities an...scikit-learn.org/stable/api/sklearn.metrics.html -
sklearn.model_selection — scikit-learn 1....
Tools for model selection, such as cross validation and hyper-parameter tuning. User guide. See the Cross-validation: evaluating estimator performance, Tuning the hyper-parameters of an estimator, ...scikit-learn.org/stable/api/sklearn.model_selection.html -
sklearn.neural_network — scikit-learn 1.8...
Models based on neural networks. User guide. See the Neural network models (supervised) and Neural network models (unsupervised) sections for further details.scikit-learn.org/stable/api/sklearn.neural_network.html -
Cross decomposition — scikit-learn 1.8.0 ...
Examples concerning the sklearn.cross_decomposition module. Compare cross decomposition methods Principal Component Regression vs Partial Least Squares Regressionscikit-learn.org/stable/auto_examples/cross_decomposition/index.html -
Frozen Estimators — scikit-learn 1.8.0 do...
Examples concerning the sklearn.frozen module. Examples of Using FrozenEstimatorscikit-learn.org/stable/auto_examples/frozen/index.html -
Nearest Neighbors — scikit-learn 1.8.0 do...
Examples concerning the sklearn.neighbors module. Approximate nearest neighbors in TSNE Caching nearest neighbors Comparing Nearest Neighbors with and without Neighborhood Components Analysis Dimen...scikit-learn.org/stable/auto_examples/neighbors/index.html -
sklearn.exceptions — scikit-learn 1.8.0 d...
Custom warnings and errors used across scikit-learn.scikit-learn.org/stable/api/sklearn.exceptions.html -
sklearn.feature_selection — scikit-learn ...
Feature selection algorithms. These include univariate filter selection methods and the recursive feature elimination algorithm. User guide. See the Feature selection section for further details.scikit-learn.org/stable/api/sklearn.feature_selection.html -
sklearn.experimental — scikit-learn 1.8.0...
Importable modules that enable the use of experimental features or estimators.scikit-learn.org/stable/api/sklearn.experimental.html