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Covariance estimation — scikit-learn 1.8.0 docu...
Examples concerning the sklearn.covariance module. Ledoit-Wolf vs OAS estimation Robust covariance estimation and Mahalanobis distances relevance Robust vs Empirical covariance estimate Shrinkage c...scikit-learn.org/stable/auto_examples/covariance/index.html -
Incremental PCA — scikit-learn 1.8.0 documentation
Incremental principal component analysis (IPCA) is typically used as a replacement for principal component analysis (PCA) when the dataset to be decomposed is too large to fit in memory. IPCA build...scikit-learn.org/stable/auto_examples/decomposition/plot_incremental_pca.html -
Developing Estimators — scikit-learn 1.8.0 docu...
Examples concerning the development of Custom Estimator.__sklearn_is_fitted__ as Developer APIscikit-learn.org/stable/auto_examples/developing_estimators/index.html -
Kernel Approximation — scikit-learn 1.8.0 docum...
Examples concerning the sklearn.kernel_approximation module. Scalable learning with polynomial kernel approximationscikit-learn.org/stable/auto_examples/kernel_approximation/index.html -
GMM covariances — scikit-learn 1.8.0 documentation
Demonstration of several covariances types for Gaussian mixture models. See Gaussian mixture models for more information on the estimator. Although GMM are often used for clustering, we can compare...scikit-learn.org/stable/auto_examples/mixture/plot_gmm_covariances.html -
sklearn.linear_model — scikit-learn 1.8.0 docum...
A variety of linear models. User guide. See the Linear Models section for further details. The following subsections are only rough guidelines: the same estimator can fall into multiple categories,...scikit-learn.org/stable/api/sklearn.linear_model.html -
Feature discretization — scikit-learn 1.8.0 doc...
A demonstration of feature discretization on synthetic classification datasets. Feature discretization decomposes each feature into a set of bins, here equally distributed in width. The discrete va...scikit-learn.org/stable/auto_examples/preprocessing/plot_discretization_classification.html -
sklearn.datasets — scikit-learn 1.8.0 documenta...
Utilities to load popular datasets and artificial data generators. User guide. See the Dataset loading utilities section for further details. Loaders: Sample generators:scikit-learn.org/stable/api/sklearn.datasets.html -
sklearn.gaussian_process — scikit-learn 1.8.0 d...
Gaussian process based regression and classification. User guide. See the Gaussian Processes section for further details. Kernels: A set of kernels that can be combined by operators and used in Gau...scikit-learn.org/stable/api/sklearn.gaussian_process.html -
sklearn.semi_supervised — scikit-learn 1.8.0 do...
Semi-supervised learning algorithms. These algorithms utilize small amounts of labeled data and large amounts of unlabeled data for classification tasks. User guide. See the Semi-supervised learnin...scikit-learn.org/stable/api/sklearn.semi_supervised.html