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1.15. Isotonic regression — scikit-learn 1.6.1 ...
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 1.6.1 ...
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 -
10. Common pitfalls and recommended practices —...
The purpose of this chapter is to illustrate some common pitfalls and anti-patterns that occur when using scikit-learn. It provides examples of what not to do, along with a corresponding correct ex...scikit-learn.org/stable/common_pitfalls.html -
Face completion with a multi-output estimators ...
This example shows the use of multi-output estimator to complete images. The goal is to predict the lower half of a face given its upper half. The first column of images shows true faces. The next ...scikit-learn.org/stable/auto_examples/miscellaneous/plot_multioutput_face_completion.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 -
SGD: Maximum margin separating hyperplane — sci...
Plot the maximum margin separating hyperplane within a two-class separable dataset using a linear Support Vector Machines classifier trained using SGD. Total running time of the script:(0 minutes 0...scikit-learn.org/stable/auto_examples/linear_model/plot_sgd_separating_hyperplane.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 -
Various Agglomerative Clustering on a 2D embedd...
An illustration of various linkage option for agglomerative clustering on a 2D embedding of the digits dataset. The goal of this example is to show intuitively how the metrics behave, and not to fi...scikit-learn.org/stable/auto_examples/cluster/plot_digits_linkage.html -
CalibrationDisplay — scikit-learn 1.6.1 documen...
Gallery examples: Comparison of Calibration of Classifiers Probability Calibration curvesscikit-learn.org/stable/modules/generated/sklearn.calibration.CalibrationDisplay.html