Feature Subset Selection with Fast Algorithm Implementation
| ||International Journal of Computer Trends and Technology (IJCTT)|| |
|© - December Issue 2013 by IJCTT Journal|
|Volume-6 Issue-1 |
|Year of Publication : 2013|
|Authors :K.Suman , S.Thirumagal|
K.Suman , S.Thirumagal"Feature Subset Selection with Fast Algorithm Implementation"International Journal of Computer Trends and Technology (IJCTT),V6(1):1-5 December Issue 2013 .ISSN 2231-2803.www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract:- -The Title “Feature Subset Selection with FAST Algorithm Implementation” has intended to show the things occurred in between the searches happened in the place of client and server. The users clearly know about the process of how to sending a request for the particular thing, and how to get a response for that request or how the system shows the results explicitly. But no one knows about the internal process of searching records from a large database. This system clearly shows how an internal process of the searching process works. In text classification, the dimensionality of the feature vector is usually huge to manage. The Problems need to be handled are as follows: a) the current problem of the existing feature clustering methods b) The desired number of extracted features has to be specified in advance c) When calculating similarities, the variance of the underlying cluster is not considered d) How to reduce the dimensionality of feature vectors for text classification and run faster. These Problems are handled by means of applying the FAST Algorithm in hands with Association Rule Mining.
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Keywords:-FAST algorithm, Feature selection, Redundant data, Text classification, Clustering, Rule mining.