Tutorial for classification by Hidden markov model

Version 1.0.0 (3.86 KB) by Selva
Basic Tutorial for classifying 1D matrix using hidden markov model for 3 class problems


Updated 30 Aug 2019

View License

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.

Cite As

Selva (2023). 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. Retrieved .

MATLAB Release Compatibility
Created with R2019a
Compatible with any release
Platform Compatibility
Windows macOS Linux

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!
Version Published Release Notes