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Ensemble methods — scikit-learn 1.6.1 documenta...
Examples concerning the sklearn.ensemble module. Categorical Feature Support in Gradient Boosting Combine predictors using stacking Comparing Random Forests and Histogram Gradient Boosting models C...scikit-learn.org/stable/auto_examples/ensemble/index.html -
Feature Selection — scikit-learn 1.6.1 document...
Examples concerning the sklearn.feature_selection module. Comparison of F-test and mutual information Model-based and sequential feature selection Pipeline ANOVA SVM Recursive feature elimination R...scikit-learn.org/stable/auto_examples/feature_selection/index.html -
Decision Trees — scikit-learn 1.6.1 documentation
Examples concerning the sklearn.tree module. Decision Tree Regression Plot the decision surface of decision trees trained on the iris dataset Post pruning decision trees with cost complexity prunin...scikit-learn.org/stable/auto_examples/tree/index.html -
Multiclass methods — scikit-learn 1.6.1 documen...
Examples concerning the sklearn.multiclass module. Overview of multiclass training meta-estimatorsscikit-learn.org/stable/auto_examples/multiclass/index.html -
Multioutput methods — scikit-learn 1.6.1 docume...
Examples concerning the sklearn.multioutput module. Multilabel classification using a classifier chainscikit-learn.org/stable/auto_examples/multioutput/index.html -
is_classifier — scikit-learn 1.6.1 documentation
Skip to main content Back to top Ctrl + K GitHub Choose version is_classifier # sklearn.base. is_classifier ( estimat...scikit-learn.org/stable/modules/generated/sklearn.base.is_classifier.html -
Sparse inverse covariance estimation — scikit-l...
Using the GraphicalLasso estimator to learn a covariance and sparse precision from a small number of samples. To estimate a probabilistic model (e.g. a Gaussian model), estimating the precision mat...scikit-learn.org/stable/auto_examples/covariance/plot_sparse_cov.html -
SGD: Weighted samples — scikit-learn 1.6.1 docu...
Plot decision function of a weighted dataset, where the size of points is proportional to its weight. Total running time of the script:(0 minutes 0.077 seconds) Launch binder Launch JupyterLite Dow...scikit-learn.org/stable/auto_examples/linear_model/plot_sgd_weighted_samples.html -
Gaussian Process for Machine Learning — scikit-...
Examples concerning the sklearn.gaussian_process module. Ability of Gaussian process regression (GPR) to estimate data noise-level Comparison of kernel ridge and Gaussian process regression Forecas...scikit-learn.org/stable/auto_examples/gaussian_process/index.html -
Two-class AdaBoost — scikit-learn 1.6.1 documen...
This example fits an AdaBoosted decision stump on a non-linearly separable classification dataset composed of two “Gaussian quantiles” clusters (see sklearn.datasets.make_gaussian_quantiles) and pl...scikit-learn.org/stable/auto_examples/ensemble/plot_adaboost_twoclass.html