Prediction of Multimodal Poisson Variable using Discretization of Gaussian Data

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F21%3A00544576" target="_blank" >RIV/67985556:_____/21:00544576 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21260/21:00350794
Result on the web
<a href="http://dx.doi.org/10.5220/0010575006000608" target="_blank" >http://dx.doi.org/10.5220/0010575006000608</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.5220/0010575006000608" target="_blank" >10.5220/0010575006000608</a>

Result language
angličtina
Original language name
Prediction of Multimodal Poisson Variable using Discretization of Gaussian Data
Original language description
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.
Czech name
—
Czech description
—

Project
<a href="/en/project/8A19009" target="_blank" >8A19009: Arrowhead Tools for Engineering of Digitalisation Solutions</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the 18th International Conference on Informatics in Control, Automation and Robotics
ISBN
978-989-758-522-7
ISSN
2184-2809
e-ISSN
—
Number of pages
9
Pages from-to
600-608
Publisher name
Scitepress
Place of publication
Setúbal
Event location
Setúbal (online)
Event date
Jul 6, 2021
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—

Similar results(10)