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Title

Analysis of Various Clustering and Classification Algorithms in Datamining

Author

Sandhia Valsala, Bindhya Thomas, Jissy Ann George

Citation

Vol. 12  No. 11  pp. 54-58

Abstract

Clustering and classification of data is a difficult problem that is related to various fields and applications. Challenge is greater, as input space dimensions become larger and feature scales are different from each other. The term “classification” is frequently used as an algorithm for all data mining tasks [1]. Instead, it is best to use the term to refer to the category of supervised learning algorithms used to search interesting data patterns. While classification algorithms have become very popular and ubiquitous in DM research, it is just but one of the many types of algorithms available to solve a specific type of DM task [12]. In this paper various clustering and classification algorithms are going to be addressed in detail. A detailed survey on existing algorithms will be made and the scalability of some of the existing classification algorithms will be examined.

Keywords

DM, clustering, classification, supervised learning, scalability

URL

http://paper.ijcsns.org/07_book/201211/20121109.pdf