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Gaussian Mixture Model Selection — scikit-learn...
Documentation for GridSearchCV i Fitted...s=2) GaussianMixture ? Documentation for GaussianMixture Parameters...scikit-learn.org/stable/auto_examples/mixture/plot_gmm_selection.html -
View web crawler events logs | App Search docum...
events logs IMPORTANT : This documentation is no longer updated. Refer...version policy and the latest documentation . View web crawler events...www.elastic.co/guide/en/app-search/current/view-web-crawler-events-logs.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 -
7.7. Kernel Approximation — scikit-learn 1.7.2 ...
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 -
1.15. Isotonic regression — scikit-learn 1.7.2 ...
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 -
1.8. Cross decomposition — scikit-learn 1.7.2 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 -
11. 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 -
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 -
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 -
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