Machine learning¶
This page lists the available machine learning models. The other feature catalogs are listed on this page.
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EQPCERegressorRegression modelAn equadratures-based polynomial chaos expansion (PCE) model.
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FCERegressorRegression modelFunctional chaos expansion model.
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GaussianMixtureClustering modelThe Gaussian mixture clustering algorithm.
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GaussianProcessRegressorRegression modelGaussian process regression model.
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GradientBoostingRegressorRegression modelGradient boosting for regression.
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KMeansClustering modelThe k-means clustering algorithm.
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KNNClassifierClassification modelThe k-nearest neighbors classification algorithm.
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LinearRegressorRegression modelLinear regression model.
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MLPRegressorRegression modelMultiLayer perceptron (MLP).
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MOERegressorRegression modelMixture of experts for regression.
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OTGaussianProcessRegressorRegression modelGaussian process regression.
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PCERegressorRegression modelPolynomial chaos expansion model.
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PolynomialRegressorRegression modelPolynomial regression model.
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RandomForestClassifierClassification modelThe random forest classification algorithm.
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RandomForestRegressorRegression modelRandom forest regression.
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RBFRegressorRegression modelRegression based on radial basis functions (RBFs).
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RegressorChainRegression modelChain regression.
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SMTRegressorRegression modelA regression model from SMT.
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SMTRegressorRegression modelA regression model from SMT.
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SVMClassifierClassification modelThe Support Vector Machine algorithm for classification.
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SVMRegressorRegression modelSupport vector machine for regression.
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TPSRegressorRegression modelThin plate spline (TPS) regression.
The data of this page were collected on 2026-09-17 from the latest version of each package.