20.500.12556/RUL-114907 Improved initialization of the EM algorithm for mixture model parameter estimation A commonly used tool for estimating the parameters of a mixture model is the Expectation-Maximization (EM) algorithm, which is an iterative procedure that can serve as a maximum-likelihood estimator. The EM algorithm has well-documented drawbacks, such as the need for good initial values and the possibility of being trapped in local optima. Nevertheless, because of its appealing properties, EM plays an important role in estimating the parameters of mixture models. To overcome these initialization problems with EM, in this paper, we propose the Rough-Enhanced-Bayes mixture estimation (REBMIX) algorithm as a more effective initialization algorithm. Three different strategies are derived for dealing with the unknown number of components in the mixture model. These strategies are thoroughly tested on artificial datasets, density-estimation datasets and image-segmentation problems and compared with state-of-the-art initialization methods for the EM. Our proposal shows promising results in terms of clustering and density-estimation performance as well as in terms of computational efficiency. All the improvements are implemented in the rebmix R package. mixture model parameter estimation EM algorithm REBMIX algorithm density estimation clustering image segmentation mešani model ocena parametrov EM algoritem REBMIX algoritem ocena gostote porazdelitev verjetnosti grozdenje segmentacija slik true false true Angleški jezik Slovenski jezik Članek v reviji 2020-03-30 14:10:39 2020-03-30 14:10:43 2022-08-27 03:58:33 0000-00-00 00:00:00 2020 0 0 29 str. iss. 3, art. 373 Vol. 8 2020 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 519.254(045) 2227-7390 10.3390/math8030373 17112347 RAZ_Panic_Branislav_2020.pdf RAZ_Panic_Branislav_2020.pdf 1 A4D1A0E3147081974A5D108768397B79 278e719f19f0c09185a775d12f61ba7ad8deaf1e0913a67dc6787eb4ee00e256 45bf4483-5664-11ec-abdb-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=151798 https://www.mdpi.com/2227-7390/8/3/373 0 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=127287 Fakulteta za strojništvo 0 0 0