期刊名称：International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
印刷版ISSN：2278-1323
出版年度：2013
卷号：2
期号：11
页码：2806-2812
出版社：Shri Pannalal Research Institute of Technolgy
摘要：Cluster analysis or clustering is the task of assigning a set of objects into groups (called clusters) so that the objects in the same cluster are more similar (in some sense or another) to each other than to those in other clusters. A cluster is intended to group objects that are related, based on observations of their attribute's values. Clustering is often confused with classification, but there is some difference between the two. In classifications the objects are assigned to pre-defined classes, where as in clustering the classes are formed. The term "class" is in fact frequently used as a synonym to the term "cluster". Clustering is used in data analysis, pattern recognition and data mining for finding unknown groups in data. This paper is intended to study and compare different clustering algorithms. The algorithms under investigation are hierarchical, partitioned; density based clustering according to the factors: methodology, structure, model, application or suitability, usefulness. Clustering is a main task of explorative, data mining and a common technique for statistical data analysis used in many fields, including machine learning, pattern recognition, image analysis, information retrieval and bio informatics.
关键词：Cluster Analysis; hierarchical clustering; ; partitioned clustering; density based clustering; Sub space ; clustering
