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Bibliografie

Monography Chapter

Practical Initialization of Recursive Mixture-Based Clustering for Non-negative Data

Suzdaleva Evženie, Nagy Ivan

: Informatics in Control, Automation and Robotics. ICINCO 2017., p. 679-698 , Eds: Gusikhin O., Madani K.

: GA15-03564S, GA ČR

: Mixture-based clustering, Recursive mixture estimation, Different components, Non-negative data, Bayesian estimation

: 10.1007/978-3-030-11292-9_34

: http://library.utia.cas.cz/separaty/2019/ZS/suzdaleva-0504124.pdf

(eng): The paper provides a practical guide on initialization of the recursive mixture-based clustering of non-negative data. For modeling the non-negative data, mixtures of uniform, exponential, gamma and other distributions can be used. Initialization is known to be an important task for a start of the mixture estimation algorithm. Within the considered recursive approach, the key point of initialization is a choice of initial statistics of the involved prior distributions. The paper describes several initialization techniques for the mentioned types of components that can be beneficial primarily from a practical point of view.

: BB

: 10103