Clustering algorithms subjected to K-mean and gaussian mixture model on multidimensional data set
Yükleniyor...
Dosyalar
Tarih
2019
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
International University of Sarajevo
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
This paper explored the method of clustering. Two main categories of algorithms will be used, namely k-means and Gaussian Mixture Model clustering. We will look at algorithms within thesis categories and what types of problems they solve, as well as what methods could be used to determine the number of clusters. Finally, we will test the algorithms out using sparse multidimensional data acquired from the usage of a video games sales all around the world, we categories the sales in three main standards of high sales, medium sales and low sales, showing that a simple implementation can achieve nontrivial results. The result will be presented in the form of an evaluation of there is potential for online clustering of video games sales. We will also discuss some task specific improvements and which approach is most suitable. © 2019 International University of Sarajevo.
Açıklama
Anahtar Kelimeler
Clustering, Data Extraction, Data Processing, Datamining, Gaussian Mixture Model, K-Means
Kaynak
Periodicals of Engineering and Natural Sciences
WoS Q Değeri
Scopus Q Değeri
Q2
Cilt
7
Sayı
2
