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get_routing_for_object — scikit-learn 1.7.2 doc...
Gallery examples: Metadata Routingscikit-learn.org/stable/modules/generated/sklearn.utils.metadata_routing.get_routing_for_object.html -
7.6. Random Projection — scikit-learn 1.7.2 doc...
The sklearn.random_projection module implements a simple and computationally efficient way to reduce the dimensionality of the data by trading a controlled amount of accuracy (as additional varianc...scikit-learn.org/stable/modules/random_projection.html -
Varying regularization in Multi-layer Perceptro...
A comparison of different values for regularization parameter ‘alpha’ on synthetic datasets. The plot shows that different alphas yield different decision functions. Alpha is a parameter for regula...scikit-learn.org/stable/auto_examples/neural_networks/plot_mlp_alpha.html -
Pipelining: chaining a PCA and a logistic regre...
The PCA does an unsupervised dimensionality reduction, while the logistic regression does the prediction. We use a GridSearchCV to set the dimensionality of the PCA, Total running time of the scrip...scikit-learn.org/stable/auto_examples/compose/plot_digits_pipe.html -
Effect of model regularization on training and ...
In this example, we evaluate the impact of the regularization parameter in a linear model called ElasticNet. To carry out this evaluation, we use a validation curve using ValidationCurveDisplay. Th...scikit-learn.org/stable/auto_examples/model_selection/plot_train_error_vs_test_error.html -
Poisson regression and non-normal loss — scikit...
This example illustrates the use of log-linear Poisson regression on the French Motor Third-Party Liability Claims dataset from 1 and compares it with a linear model fitted with the usual least squ...scikit-learn.org/stable/auto_examples/linear_model/plot_poisson_regression_non_normal_loss.html -
Lasso model selection via information criteria ...
This example reproduces the example of Fig. 2 of[ZHT2007]. A LassoLarsIC estimator is fit on a diabetes dataset and the AIC and the BIC criteria are used to select the best model. References ZHT200...scikit-learn.org/stable/auto_examples/linear_model/plot_lasso_lars_ic.html -
Swiss Roll And Swiss-Hole Reduction — scikit-le...
This notebook seeks to compare two popular non-linear dimensionality techniques, T-distributed Stochastic Neighbor Embedding (t-SNE) and Locally Linear Embedding (LLE), on the classic Swiss Roll da...scikit-learn.org/stable/auto_examples/manifold/plot_swissroll.html -
Explicit feature map approximation for RBF kern...
An example illustrating the approximation of the feature map of an RBF kernel. It shows how to use RBFSampler and Nystroem to approximate the feature map of an RBF kernel for classification with an...scikit-learn.org/stable/auto_examples/miscellaneous/plot_kernel_approximation.html -
1.7. Gaussian Processes — scikit-learn 1.7.2 do...
Gaussian Processes (GP) are a nonparametric supervised learning method used to solve regression and probabilistic classification problems. The advantages of Gaussian processes are: The prediction i...scikit-learn.org/stable/modules/gaussian_process.html