TY - CHAP
T1 - A survey of Clustering Algorithms.
AU - Rokach, Lior
N1 - DBLP License: DBLP's bibliographic metadata records provided through http://dblp.org/ are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.
PY - 2010/7/7
Y1 - 2010/7/7
N2 - This chapter presents a tutorial overview of the main clustering methods used in Data Mining. The goal is to provide a self-contained review of the concepts and the mathematics underlying clustering techniques. The chapter begins by providing measures and criteria that are used for determining whether two objects are similar or dissimilar. Then the clustering methods are presented, divided into: hierarchical, partitioning, density-based, model-based, grid-based, and soft-computing methods. Following the methods, the challenges of performing clustering in large data sets are discussed. Finally, the chapter presents how to determine the number of clusters.
AB - This chapter presents a tutorial overview of the main clustering methods used in Data Mining. The goal is to provide a self-contained review of the concepts and the mathematics underlying clustering techniques. The chapter begins by providing measures and criteria that are used for determining whether two objects are similar or dissimilar. Then the clustering methods are presented, divided into: hierarchical, partitioning, density-based, model-based, grid-based, and soft-computing methods. Following the methods, the challenges of performing clustering in large data sets are discussed. Finally, the chapter presents how to determine the number of clusters.
KW - Clustering
KW - K-means
KW - Intra-cluster homogeneity
KW - Inter-cluster separability
U2 - 10.1007/978-0-387-09823-4_14
DO - 10.1007/978-0-387-09823-4_14
M3 - Chapter
SN - 978-0-387-09822-7
SP - 269
EP - 298
BT - Data Mining and Knowledge Discovery Handbook
PB - Springer, Boston, MA
ER -