Optimal number of clusters provided by k-means and E-M algorithm (CROSBI ID 643725)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Novoselac, Vedran ; Pavić, Zlatko
engleski
Optimal number of clusters provided by k-means and E-M algorithm
The paper considers the problem of determining the optimal number of clusters in data set by grouping index. The problem of clustering are provided with k-means and E-M (Expectation Maximization) algorithm. In addition to well- known indexes that are frequently used, two new indexes are presented. New indexes are based on the orthogonal distances from data to the line which represent corresponding cluster in the partition obtained with mentioned algorithms.
k-means ; expectation maximization ; grouping index
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
Podaci o prilogu
286-291.
2016.
nije evidentirano
objavljeno
9788080962371
Podaci o matičnoj publikaciji
Proceedings of 8th International Scientific and Expert Conference of the International TEAM Society
AlumniPress
Trnava: Faculty of Materials Science and Technology in Trnava
Podaci o skupu
8th International Scientific and Expert Conference of the International TEAM Society
ostalo
19.10.2016-21.10.2016
Trnava, Slovačka