DBSCAN,OPTICS ve K-means kümeleme algoritmalarının uygulamalı karşılaştırılması

Bu çalışmada, veri madenciliğinde güncel kümeleme algoritmalarından DBSCAN, OPTICS ile geçmişi daha eskilere dayanan K-means algoritması karşılaştırılmıştır. Karşılaştırma sentetik veritabanı üzerinde gösterdikleri küme bulma performansları değerlendirilerek yapılmıştır. Sonuçta, yakın zamanda literatüre giren DBSCAN ve OPTICS algoritmalarının K-means algoritmasından daha üstün küme oluşturma özelliklerine sahip olduğu tespit edilmiştir.

Applied comparison of DBSCAN,OPTICS and K-means clustering algorithms

DBSCAN and OPTICS are two recent clustering algorithms on data mining. In this study, these two algorithms and K-means which is one of the oldest clustering algorithms are compared. Comparison is based on cluster discovery performance on synthetic database. Consequently, two recent clustering algorithms DBSCAN and OPTICS are performed superior accuracy and cluster discovery ability over K-means algorithm.

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