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sklearn.linear_model — scikit-learn 1.8.0...
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 -
Covariance estimation — scikit-learn 1.8....
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 1.8....
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...
Examples concerning the sklearn.kernel_approximation module. Scalable learning with polynomial kernel approximationscikit-learn.org/stable/auto_examples/kernel_approximation/index.html -
sklearn.cross_decomposition — scikit-lear...
Algorithms for cross decomposition. User guide. See the Cross decomposition section for further details.scikit-learn.org/stable/api/sklearn.cross_decomposition.html -
sklearn.discriminant_analysis — scikit-le...
Linear and quadratic discriminant analysis. User guide. See the Linear and Quadratic Discriminant Analysis section for further details.scikit-learn.org/stable/api/sklearn.discriminant_analysis.html -
sklearn.isotonic — scikit-learn 1.8.0 doc...
Isotonic regression for obtaining monotonic fit to data. User guide. See the Isotonic regression section for further details.scikit-learn.org/stable/api/sklearn.isotonic.html -
sklearn.semi_supervised — scikit-learn 1....
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 -
Decision Tree Regression with AdaBoost — ...
color = colors [ 1 ], label = "n_estimators=1" , linewidth...boosted using the AdaBoost.R2 [ 1 ] algorithm on a 1D sinusoidal...scikit-learn.org/stable/auto_examples/ensemble/plot_adaboost_regression.html -
Support Vector Regression (SVR) using linear an...
1.1 ), ncol = 1 , fancybox = True , shadow..., C = 100 , gamma = 0.1 , epsilon = 0.1 ) svr_lin = SVR ( kernel...scikit-learn.org/stable/auto_examples/svm/plot_svm_regression.html