Tutorial for classification by Hidden markov model

Versión 1.0.0 (3,86 KB) por Selva
Basic Tutorial for classifying 1D matrix using hidden markov model for 3 class problems
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Actualizado 30 ago 2019

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1D matrix classification using hidden markov model based machine learning for 3 class problems. It also consist of a matrix-based example of input sample of size 15 and 3 features



needs toolbox
Hidden Markov Model (HMM) Toolbox for Matlab
Written by Kevin Murphy, 1998.
Last updated: 8 June 2005.
Distributed under the MIT License

This toolbox supports inference and learning for HMMs with discrete outputs (dhmm's), Gaussian outputs (ghmm's), or mixtures of Gaussians output (mhmm's). The Gaussians can be full, diagonal, or spherical (isotropic). It also supports discrete inputs, as in a POMDP. The inference routines support filtering, smoothing, and fixed-lag smoothing.

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Selva (2024). Tutorial for classification by Hidden markov model (https://www.mathworks.com/matlabcentral/fileexchange/72594-tutorial-for-classification-by-hidden-markov-model), MATLAB Central File Exchange. Recuperado .

Compatibilidad con la versión de MATLAB
Se creó con R2019a
Compatible con cualquier versión
Compatibilidad con las plataformas
Windows macOS Linux
Más información sobre Markov Chain Models en Help Center y MATLAB Answers.

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