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Incremental PCA — scikit-learn 1.7.2 docu...
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 -
Covariance estimation — scikit-learn 1.7....
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 -
Developing Estimators — scikit-learn 1.7....
Examples concerning the development of Custom Estimator.__sklearn_is_fitted__ as Developer APIscikit-learn.org/stable/auto_examples/developing_estimators/index.html -
7.7. Kernel Approximation — scikit-learn ...
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 -
An example of K-Means++ initialization — ...
An example to show the output of the sklearn.cluster.kmeans_plusplus function for generating initial seeds for clustering. K-Means++ is used as the default initialization for K-means. Total running...scikit-learn.org/stable/auto_examples/cluster/plot_kmeans_plusplus.html -
Plot the support vectors in LinearSVC — s...
Unlike SVC (based on LIBSVM), LinearSVC (based on LIBLINEAR) does not provide the support vectors. This example demonstrates how to obtain the support vectors in LinearSVC. Total running time of th...scikit-learn.org/stable/auto_examples/svm/plot_linearsvc_support_vectors.html -
OOB Errors for Random Forests — scikit-le...
The RandomForestClassifier is trained using bootstrap aggregation, where each new tree is fit from a bootstrap sample of the training observations z_i = (x_i, y_i). The out-of-bag(OOB) error is the...scikit-learn.org/stable/auto_examples/ensemble/plot_ensemble_oob.html -
Plot Hierarchical Clustering Dendrogram —...
This example plots the corresponding dendrogram of a hierarchical clustering using AgglomerativeClustering and the dendrogram method available in scipy. Total running time of the script:(0 minutes ...scikit-learn.org/stable/auto_examples/cluster/plot_agglomerative_dendrogram.html -
1.15. Isotonic regression — scikit-learn ...
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...
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