Challenges and possible solutions to density based clustering
Bildiriler > Tam Metin Bildiri · 2016
Yazarlar: Fatma Gunseli Yasar, Gözde ULUTAGAY
8th IEEE International Conference on Intelligent Systems, IS 2016, Amerika Birleşik Devletleri, Sofia, Uluslararası, Davetli Konuşmacı, Tam Metin Bildiri, 2016-2016, ss 492-498
Özet
Clustering is an interdisciplinary-studied subject of statistical data analysis. In this study, among various types of clustering algorithms, the algorithms derived from Density Based Spatial Clustering of Applications with Noise (DBSCAN) are investigated. Although DBSCAN is the well-known density-based algorithms it has some bottlenecks. So, enhanced versions of DBSCAN are developed to provide some solutions and to ameliorate the algorithm. In this study, we provide a compact source of DBSCAN-based algorithms for the mentioned challenges.