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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 -
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 -
get_routing_for_object — scikit-learn 1.5.2 doc...
Gallery examples: Metadata Routingscikit-learn.org/stable/modules/generated/sklearn.utils.metadata_routing.get_routing_for_object.html -
1.8. Cross decomposition — scikit-learn 1.5.2 d...
The cross decomposition module contains supervised estimators for dimensionality reduction and regression, belonging to the “Partial Least Squares” family. Cross decomposition algorithms find the f...scikit-learn.org/stable/modules/cross_decomposition.html -
1.15. Isotonic regression — scikit-learn 1.5.2 ...
The class IsotonicRegression fits a non-decreasing real function to 1-dimensional data. It solves the following problem:\min \sum_i w_i (y_i - \hat{y}_i)^2 subject to\hat{y}_i \le \hat{y}_j wheneve...scikit-learn.org/stable/modules/isotonic.html -
6.7. Kernel Approximation — scikit-learn 1.5.2 ...
This submodule contains functions that approximate the feature mappings that correspond to certain kernels, as they are used for example in support vector machines (see Support Vector Machines). Th...scikit-learn.org/stable/modules/kernel_approximation.html -
Comparing different clustering algorithms on to...
This example shows characteristics of different clustering algorithms on datasets that are “interesting” but still in 2D. With the exception of the last dataset, the parameters of each of these dat...scikit-learn.org/stable/auto_examples/cluster/plot_cluster_comparison.html -
SVM: Separating hyperplane for unbalanced class...
Find the optimal separating hyperplane using an SVC for classes that are unbalanced. We first find the separating plane with a plain SVC and then plot (dashed) the separating hyperplane with automa...scikit-learn.org/stable/auto_examples/svm/plot_separating_hyperplane_unbalanced.html -
Comparison of F-test and mutual information — s...
This example illustrates the differences between univariate F-test statistics and mutual information. We consider 3 features x_1, x_2, x_3 distributed uniformly over [0, 1], the target depends on t...scikit-learn.org/stable/auto_examples/feature_selection/plot_f_test_vs_mi.html -
Cross-validation on diabetes Dataset Exercise —...
A tutorial exercise which uses cross-validation with linear models. This exercise is used in the cv_estimators_tut part of the model_selection_tut section of the stat_learn_tut_index. Load dataset ...scikit-learn.org/stable/auto_examples/exercises/plot_cv_diabetes.html