TITLE

Analysis of Various Clustering and Classification Algorithms in Datamining

AUTHOR(S)
Valsala, Sandhia; Thomas, Bindhya; George, Jissy Ann
PUB. DATE
November 2012
SOURCE
International Journal of Computer Science & Network Security;Nov2012, Vol. 12 Issue 11, p54
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
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.
ACCESSION #
84029279

 

Share

Read the Article

Courtesy of THE LIBRARY OF VIRGINIA

Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics