International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 171 - Number 2 |
Year of Publication: 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
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.