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 
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/
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     author = {Dangalchev, Chavdar},
     title = {Using entropy of categorical data for clustering},
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     series = {Mathematics and Education in Mathematics},
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     year = {2020},
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     language = {en},
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