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Decision Trees — scikit-learn 1.8.0 docum...
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 -
Feature Selection — scikit-learn 1.8.0 do...
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 -
SGD: Penalties — scikit-learn 1.8.0 docum...
Contours of where the penalty is equal to 1 for the three penalties L1, L2 and elastic-net. All of the above are supported by SGDClassifier and SGDRegressor. Total running time of the script:(0 min...scikit-learn.org/stable/auto_examples/linear_model/plot_sgd_penalties.html -
Release Highlights for scikit-learn 1.2 —...
Documentation for HistGradientBoosting...HistGradientBoosting ? Documentation for HistGradientBoosting...scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_2_0.html -
Sparse inverse covariance estimation — sc...
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 -
Early stopping in Gradient Boosting — sci...
Gradient Boosting is an ensemble technique that combines multiple weak learners, typically decision trees, to create a robust and powerful predictive model. It does so in an iterative fashion, wher...scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_early_stopping.html -
Agglomerative clustering with different metrics...
Demonstrates the effect of different metrics on the hierarchical clustering. The example is engineered to show the effect of the choice of different metrics. It is applied to waveforms, which can b...scikit-learn.org/stable/auto_examples/cluster/plot_agglomerative_clustering_metrics.html -
3. Model selection and evaluation — sciki...
Cross-validation: evaluating estimator performance- Computing cross-validated metrics, Cross validation iterators, A note on shuffling, Cross validation and model selection, Permutation test score....scikit-learn.org/stable/model_selection.html -
Non-negative least squares — scikit-learn...
In this example, we fit a linear model with positive constraints on the regression coefficients and compare the estimated coefficients to a classic linear regression. Generate some random data Spli...scikit-learn.org/stable/auto_examples/linear_model/plot_nnls.html -
Gaussian Process for Machine Learning — s...
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