Quality evaluation of clustering algorithms
Автор: Bilgaeva L.P., Sambyalov Z.G.
Журнал: Вестник Восточно-Сибирского государственного университета технологий и управления @vestnik-esstu
Статья в выпуске: 6 (45), 2013 года.
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This article describes the most well-known and widely used clustering algorithms designed to handle numerical and categorical data. Algorithms were tested on artificial and real data. According to test results clustering quality assessment and scenario of clustering algorithms with a view of their application for both categorical and numerical data is proposed.
Data mining, clustering, clustering quality criteria, clustering quality index
Короткий адрес: https://sciup.org/142142800
IDR: 142142800
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