Recursive Clustering Hematological Data Using Mixture of Exponential Components

0482566 - ÚTIA 2018 RIV JP eng C - Conference Paper (international conference)
Suzdaleva, Evgenia - Nagy, Ivan - Petrouš, Matej
Recursive Clustering Hematological Data Using Mixture of Exponential Components.
Proceedings of International Conference on Intelligent Informatics and BioMedical Sciences ICIIBMS 2017. Piscataway: IEEE, 2017, s. 63-70. ISBN 978-1-5090-6665-0.
[International Conference on Intelligent Informatics and BioMedical Sciences ICIIBMS 2017. Okinawa (JP), 24.11.2017-26.11.2017]
R&D Projects: GA ČR GA15-03564S
Institutional support: RVO:67985556
Keywords : mixture-based clustering * recursive mixture estimation * exponential components
OECD category: Statistics and probability
http://library.utia.cas.cz/separaty/2017/ZS/suzdaleva-0482566.pdf

The paper deals with the mixture-based clustering of anonymized data of patients with leukemia. The presented clustering algorithm is based on the recursive Bayesian mixture estimation for the case of exponential components and the data-dependent dynamic pointer model. The main contribution of the paper is the online performance of clustering, which allows us to actualize the statistics of components and the pointer model with each new measurement. Results of the application of the algorithm to the clustering of hematological data are demonstrated and compared with theoretical counterparts.

Permanent Link: http://hdl.handle.net/11104/0278141