The statlearn toolbox: statistical learning tools for Matlab. Main features: Unsupervised Learning: Multidimensional distributions, parametric density models (or generative models), Mixture distributions, Learning/estimating the parameters: Standard Maximum Likelihood estimators, EM algorithm for latent class models, Conjugate Gradient descent other probabilty models, Model Selection (BIC criterion). Supervised Learning: Support Vector Machines (in conjunction with OSU-SVM toolbox), K Nearest Neighbors (KNN) classification method, Generative classifiers (also called Bayesian Classifiers), including Linear and Quadratic Discriminant Analysis, Mixture Discriminant Analysis; Model Selection, using Cross-Validation or other criterions.

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References in zbMATH (referenced in 1 article )

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  1. Bouveyron, Charles; Brunet-Saumard, Camille: Model-based clustering of high-dimensional data: a review (2014)