Clustering with a Model of Sub-Mixtures of Different Distributions

0478195 - ÚTIA 2018 RIV US eng C - Konferenční příspěvek (zahraniční konf.)
Nagy, Ivan - Suzdaleva, Evgenia - Petrouš, Matej
Clustering with a Model of Sub-Mixtures of Different Distributions.
Proceedings of IEEE 15th International Symposium on Intelligent Systems and Informatics SISY 2017. Piscataway: IEEE, 2017, s. 315-320. ISBN 978-1-5386-3854-5.
[IEEE 15th International Symposium on Intelligent Systems and Informatics (SISY 2017). Subotica (RS), 14.09.2017-16.09.2017]
Grant CEP: GA ČR GA15-03564S
Institucionální podpora: RVO:67985556
Klíčová slova: clustering * sub-mixtures * different distributions
Obor OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
http://library.utia.cas.cz/separaty/2017/ZS/nagy-0478195.pdf

This paper deals with a modeling of data by several mixtures of different distributions within a task of clustering. This issue can be required from a practical point of view, e.g., for a multi-modal system, which generates measurements described by different distributions. The approach is based on the partition of the data on several parts, the factorization of the joint probability density function according to these parts and the estimation of each conditional mixture separately. Due to the data-based construction of the general model from the estimated components, the most suitable combination of the components is used at each time instant. The illustrative experiments are demonstrated.
Trvalý link: http://hdl.handle.net/11104/0274423