MixRHLP_Matlab_v1
This toolbox contains the codes of the expectation-maximization algorithms to infer the mixture models for functional data (time series) clustering and optimal segmentation: mixture of regression models with hidden logistic processes.
For more details, see the papers mentioned in the references sections.
Additional toolboxes for time series segmentation and clustering, unsupervised learning of mixture models will also be provided soon.
Cite As
Faicel Chamroukhi (2024). MixRHLP_Matlab_v1 (https://github.com/fchamroukhi/MixRHLP_m), GitHub. Retrieved .
@article{Chamroukhi-RHLP-2009, Author = {Chamroukhi, F. and Sam\'{e}, A. and Govaert, G. and Aknin, P.}, Journal = {Neural Networks}, Number = {5-6}, Pages = {593--602}, Publisher = {Elsevier Science Ltd.}, Title = {Time series modeling by a regression approach based on a latent process}, Volume = {22}, Year = {2009} } @article{Chamroukhi-MixRHLP-2011, Author = {Sam{\'e}, A. and Chamroukhi, F. and Govaert, G{\'e}rard and Aknin, P.}, Issue = 4, Journal = {Advances in Data Analysis and Classification}, Pages = {301--321}, Publisher = {Springer Berlin / Heidelberg}, Title = {Model-based clustering and segmentation of time series with changes in regime}, Volume = 5, Year = {2011} } @article{Chamroukhi-RHLP-FLDA, Author = {Chamroukhi, F. and Sam\'{e}, A. and Govaert, G. and Aknin, P.}, Journal = {Neurocomputing}, Number = {7-9}, Pages = {1210--1221}, Title = {A hidden process regression model for functional data description. Application to curve discrimination}, Volume = {73}, Year = {2010} } @article{Chamroukhi-FMDA-2013, Author = {Chamroukhi, F. and Glotin, H. and Sam{\'e}, A.}, Journal = {Neurocomputing}, Pages = {153-163}, Title = {Model-based functional mixture discriminant analysis with hidden process regression for curve classification}, Volume = {112}, Year = {2013} } @article{Chamroukhi-FDA-2018, Journal = {}, Author = {Faicel Chamroukhi and Hien D. Nguyen}, Volume = {}, Title = {Model-Based Clustering and Classification of Functional Data}, Year = {2018}, note={arXiv:1803.00276v2} }
MATLAB Release Compatibility
Platform Compatibility
Windows macOS LinuxCategories
Tags
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!Discover Live Editor
Create scripts with code, output, and formatted text in a single executable document.
Versions that use the GitHub default branch cannot be downloaded
Version | Published | Release Notes | |
---|---|---|---|
1.0.0 |
|