Geodesic
Using entropy of categorical data for clustering
Mathematics and Education in Mathematics, Tome 49 (2020), pp. 133-136.

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One of the most important tasks of cluster analysis is determining the number of clusters. In this article we suggest a method for it, using entropy of categorical data. Examples, illustrating the method, are given. Една от най-важните задачи при клъстърния анализ е определяне на броя на клъстърите. В тази статия предлагаме метод, който използва ентропия на категорийни данни. Прилагат се примери, илюстриращи този метод.
Keywords: clustering, entropy, number of clusters, 62H30, 68T10, клъстърен анализ, ентропия, брой на клъстърите, 62H30, 68T10 
@article{MEM_2020_49_a12,
     author = {Dangalchev, Chavdar},
     title = {Using entropy of categorical data for clustering},
     journal = {Mathematics and Education in Mathematics},
     pages = {133--136},
     publisher = {mathdoc},
     volume = {49},
     year = {2020},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/MEM_2020_49_a12/}
}
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Dangalchev, Chavdar. Using entropy of categorical data for clustering. Mathematics and Education in Mathematics, Tome 49 (2020), pp. 133-136. http://geodesic.mathdoc.fr/item/MEM_2020_49_a12/