Bibliografie
Conference Paper (international conference)
Mixture-based Clustering Non-gaussian Data with Fixed Bounds
, ,
: Proceedings of 2016 IEEE 8th International Conference on Intelligent Systems, p. 265-271
: 2016 IEEE 8th International Conference on Intelligent Systems IS'2016, (Sofia, BG, 04.09.2016-06.09.2016)
: GA15-03564S, GA ČR
: mixture-based clustering, recursive mixture estimation, mixture of uniform distributions, data-dependent pointer
: http://library.utia.cas.cz/separaty/2016/ZS/suzdaleva-0462336.pdf
(eng): This paper deals with clustering non-gaussian data with fixed bounds. It considers the problem using recursive mixture estimation algorithms under the Bayesian methodology. Such a solution is often desired in areas, where the assumption of normality of modeled data is rather questionable and brings a series of limitations (e.g., non-negative, bounded data, etc.). Here for modeling the data a mixture of uniform distributions is taken, where individual clusters are described by mixture components. For the on-line detection of clusters of measured bounded data, the paper proposes a mixture estimation algorithm based on (i) the update of reproducible statistics of uniform components; (ii) the heuristic initialization via the method of moments; (iii) the non-trivial adaptive forgetting technique; (iv) the data-dependent dynamic pointer model. The approach is validated using realistic traffic flow simulations.
: BB