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Bibliography

Conference Paper (international conference)

Modeling of mixed data for Poisson prediction

Petrouš Matej, Uglickich Evženie

: Applied Computational Intelligence and Informatics (SACI) : 2020 IEEE 14th International Symposium on Applied Computational Intelligence and Informatics (SACI), p. 77-82

: IEEE 14th International Symposium on Applied Computational Intelligence and Informatics SACI 2020, (Timisoara, RO, 20200521)

: 8A17006, GA MŠk

: mixed data, Poisson distribution, mixture based clustering, passenger demand

: 10.1109/SACI49304.2020.9118836

: http://library.utia.cas.cz/separaty/2020/AS/uglickich-0524975.pdf

(eng): The paper deals with the task of modeling mixed continuous Gaussian and discrete Poisson data observed on a multimodal system. The proposed solution is based on recursive algorithms of Bayesian mixture estimation. The main contributions of the approach are: (i) the use of the discretized information of normal variables in the form of their clusters in order to keep the one-pass recursive estimation methodology and (ii) the prediction of the multimodal Poisson variable. Experiments with simulated and real data are presented.

: BB

: 10103