Challenges and possible solutions to density based clustering
Conference paper > Full Text · 2016
Authors: Fatma Gunseli Yasar, Gözde ULUTAGAY
8th IEEE International Conference on Intelligent Systems, IS 2016, United States of America, Sofia, International, Invitee, Full Text, 2016-2016, pp 492-498
Summary
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.