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Univariate Feature Selection — scikit-learn 1.5...
This notebook is an example of using univariate feature selection to improve classification accuracy on a noisy dataset. In this example, some noisy (non informative) features are added to the iris...scikit-learn.org/stable/auto_examples/feature_selection/plot_feature_selection.html -
Species distribution modeling — scikit-learn 1....
Modeling species’ geographic distributions is an important problem in conservation biology. In this example, we model the geographic distribution of two South American mammals given past observatio...scikit-learn.org/stable/auto_examples/applications/plot_species_distribution_modeling.html -
Digits Classification Exercise — scikit-learn 1...
A tutorial exercise regarding the use of classification techniques on the Digits dataset. This exercise is used in the clf_tut part of the supervised_learning_tut section of the stat_learn_tut_inde...scikit-learn.org/stable/auto_examples/exercises/plot_digits_classification_exercise.html -
k_means — scikit-learn 1.5.2 documentation
Skip to main content Back to top Ctrl + K GitHub k_means # sklearn.cluster. k_means ( X , n_clusters , * , sample_wei...scikit-learn.org/stable/modules/generated/sklearn.cluster.k_means.html -
calibration_curve — scikit-learn 1.5.2 document...
Skip to main content Back to top Ctrl + K GitHub calibration_curve # sklearn.calibration. calibration_curve ( y_true ...scikit-learn.org/stable/modules/generated/sklearn.calibration.calibration_curve.html -
GMM Initialization Methods — scikit-learn 1.5.2...
Examples of the different methods of initialization in Gaussian Mixture Models See Gaussian mixture models for more information on the estimator. Here we generate some sample data with four easy to...scikit-learn.org/stable/auto_examples/mixture/plot_gmm_init.html -
Support Vector Machines — scikit-learn 1.5.2 do...
Examples concerning the sklearn.svm module. One-class SVM with non-linear kernel (RBF) Plot classification boundaries with different SVM Kernels Plot different SVM classifiers in the iris dataset P...scikit-learn.org/stable/auto_examples/svm/index.html -
Kernel Density Estimation — scikit-learn 1.5.2 ...
This example shows how kernel density estimation (KDE), a powerful non-parametric density estimation technique, can be used to learn a generative model for a dataset. With this generative model in ...scikit-learn.org/stable/auto_examples/neighbors/plot_digits_kde_sampling.html -
SVM with custom kernel — scikit-learn 1.5.2 doc...
Simple usage of Support Vector Machines to classify a sample. It will plot the decision surface and the support vectors. Total running time of the script:(0 minutes 0.093 seconds) Launch binder Lau...scikit-learn.org/stable/auto_examples/svm/plot_custom_kernel.html -
config_context — scikit-learn 1.5.2 documentation
Gallery examples: Introducing the set_output APIscikit-learn.org/stable/modules/generated/sklearn.config_context.html