statlearn

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.

Keywords for this software

Anything in here will be replaced on browsers that support the canvas element


References in zbMATH (referenced in 1 article )

Showing result 1 of 1.
Sorted by year (citations)

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