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Unsupervised REgression MIXtures (uReMix)
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Functional_data_examples
.DS_Store
MAP.m
README.md
RandIndex.m
bsplinebasis.m
designmatrix_Poly_Reg.m
em_RE_PRM.m
evaluation.m
initialize_MixReg.m
load_functional_dataset.m
log_normalize.m
logdet.m
logsumexp.m
main.m
plot_results_robust_em_RM.m
robust_em_PRM.m
robust_em_PSRM.m
robust_em_RE_PRM.m
robust_em_RE_PSRM.m
splinebasis.m
tight_subplot.m

README.md

Scripts for (curve) clustering with Regression Mixtures (polynomial, spline, B-spline, with mixed random effects) and the robust EM algorithm. The algorithm simultaneously estimates the model parameters, and the number of mixture components, by a regularized likelihood estimation approach. Please cite the following papers and this code when using it:

  • F. Chamroukhi. Unsupervised learning of regression mixture models with unknown number of components. Journal of Statistical Computation and Simulation Taylor & Francis Online., Vol. 86, pages:2308-2334, Nov, 2016
  • F. Chamroukhi. Robust EM algorithm for model-based curve clustering., pages:1-8, August, 2013, Proceedings of the International Joint Conference on Neural Networks (IJCNN), IEEE

(c) by F. Chamroukhi

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