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Conference Paper (international conference)

Prediction of Multimodal Poisson Variable using Discretization of Gaussian Data

Uglickich Evženie, Nagy Ivan, Petrouš Matej

: Proceedings of the 18th International Conference on Informatics in Control, Automation and Robotics, p. 600-608 , Eds: Gusikhin O., Nijmeijer H., Madani K.

: International Conference on Informatics in Control, Automation and Robotics 2021 /18./, (Setúbal (online), PT, 20210706)

: 8A19009, GA MŠk

: Poisson Distribution Prediction, Discrete Data, Discretization, Mixture based Clustering, Bayesian Recursive Mixture Estimation

: 10.5220/0010575006000608


(eng): The paper deals with predicting a discrete target variable described by the Poisson distribution based on the discretized Gaussian explanatory data under condition of the multimodality of a system observed. The discretization is performed using the recursive mixture-based clustering algorithms under Bayesian methodology. The proposed approach allows to estimate the Gaussian and Poisson models existing for each discretization interval of explanatory data and use them for the prediction. The main contributions of the approach include: (i) modeling the Poisson variable based on the cluster analysis of explanatory continuous data, (ii) the discretization approach based on recursive mixture estimation theory, (iii) the online prediction of the Poisson variable based on available Gaussian data discretized in real time. Results of illustrative experiments and comparison with the Poisson regression is demonstrated.

: BB

: 10103