Overview of Different Methods Used in Clustering Algorithms

Yıl 2020, Cilt: 3 Sayı: 4, 173 - 189, 01.10.2020

Tohid Yousefi , Mehmet Serhat Odabas , Recai Oktaş

https://doi.org/10.34248/bsengineering.698741

Öz

Data mining is the process of extracting meaningful information from large databases using many techniques and algorithms. Data mining is often referred to as "information discovery in data" and many methods are used to find this information. Clustering method, which is one of the basic methods of data mining, is one of the most powerful methods to analyze these data, while data is being produced rapidly in today's world. Clustering is the technique of finding natural groupings or clusters in data based on some similarity distances. Also clustering is essentially a fundamental step in many different data analyzes. Therefore, different methods used in clustering algorithms are briefly described in this review.

Anahtar Kelimeler

Algorithm, Clustering, Partitional clustering, Density-based clustering, Hierarchical clustering

Kümeleme Algoritmalarında Kullanılan Farklı Yöntemlere Genel Bakış

Öz

Veri madenciliği, birçok teknik ve algoritmayı kullanarak büyük veri tabanlarından anlamlı bilgileri çıkarma işlemidir. Veri madenciliği genellikle, “verilerde bilgi keşfi” olarak adlandırılan ve bu bilgileri bulmak için kullanılan yöntemlerdir. Veri madenciliğinin temel yöntemlerinden birisi olan kümeleme yöntemidir. Kümeleme yöntemi günümüz dünyasında hızla çoğalan verilerin analizinde kullanılacak en güçlü yöntemlerdendir. Kümeleme bazı benzerlik mesafelerine dayalı olarak verilerdeki doğal gruplamaları veya kümeleri bulma tekniğidir. Kümeleme aslında birçok farklı veri analizlerinde temel bir adımdır. Bundan dolayı bu derlemede kümeleme algoritmalarında kullanılan farklı yöntemler özet bir şekilde anlatılmıştır.

Anahtar Kelimeler

Algoritma, Kümeleme, Hiyerarşik kümeleme, Bölümsel Kümeleme, Yoğunluk tabanlı kümeleme

Kaynakça

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