Research Article
Prescient Precision Utilizing GABASS Approach over Bank Data
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 171 - Issue 2 |
| Published: Aug 2017 |
| Authors: Kanika Choudhary, Jaykant Pratap Singh Yadav, Pradeep Kumar |
10.5120/ijca2017914987
|
Kanika Choudhary, Jaykant Pratap Singh Yadav, Pradeep Kumar . Prescient Precision Utilizing GABASS Approach over Bank Data. International Journal of Computer Applications. 171, 2 (Aug 2017), 27-30. DOI=10.5120/ijca2017914987
@article{ 10.5120/ijca2017914987,
author = { Kanika Choudhary,Jaykant Pratap Singh Yadav,Pradeep Kumar },
title = { Prescient Precision Utilizing GABASS Approach over Bank Data },
journal = { International Journal of Computer Applications },
year = { 2017 },
volume = { 171 },
number = { 2 },
pages = { 27-30 },
doi = { 10.5120/ijca2017914987 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2017
%A Kanika Choudhary
%A Jaykant Pratap Singh Yadav
%A Pradeep Kumar
%T Prescient Precision Utilizing GABASS Approach over Bank Data%T
%J International Journal of Computer Applications
%V 171
%N 2
%P 27-30
%R 10.5120/ijca2017914987
%I Foundation of Computer Science (FCS), NY, USA
Abstract
For improving accuracy in present work experiment is proposed over bank data to classify, according to the 11 existing feature. Classification problems frequently have a large number of features, but not all of them are utile for classification. Redundant and irrelevant features may be reduced the classification accuracy. Feature selection is a procedure of choosing a subset of significant components, which can diminish the dimensionality, abbreviate the running time. Genetic algorithm as an optimization tool and Naïve Bayes classifier will be used to compute the accuracy.
References
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