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Research of nonparametric density estimation algorithms by applying clustering methods
- Source :
- Lietuvos Matematikos Rinkinys, Vol 46, Iss spec. (2023)
- Publication Year :
- 2023
- Publisher :
- Vilnius University Press, 2023.
-
Abstract
- One of the ways to improve the accuracy of probability density estimation is multi-mode density treating as the mixture of single-mode one. In this paper we offer to use data clustering in the first place and to estimate density in every cluster separately. To objectively compare the performance, Monte Carlo approximation is used. While using various methods to evaluate the accuracy of probability density estimations we tried to use clustered and not clustered data. In this paper we also tried to reveal the usefulness of using clustering for data generated by single-mode and multi-mode distributions.
Details
- Language :
- English, Lithuanian
- ISSN :
- 01322818 and 2335898X
- Volume :
- 46
- Issue :
- spec.
- Database :
- Directory of Open Access Journals
- Journal :
- Lietuvos Matematikos Rinkinys
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.0d7b6468530d4f4bbafea6f077746290
- Document Type :
- article
- Full Text :
- https://doi.org/10.15388/LMR.2006.30726