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An Analytical Comparison on Filter Feature Extraction Method in Data Mining using J48 Classifier
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 124 - Number 13 |
| Year of Publication: 2015 |
| Authors: Abdur Rahman Onik, Nutan Farah Haq, Lamia Alam, Tauseef Ibne Mamun |
10.5120/ijca2015905706
|
Abdur Rahman Onik, Nutan Farah Haq, Lamia Alam, Tauseef Ibne Mamun . An Analytical Comparison on Filter Feature Extraction Method in Data Mining using J48 Classifier. International Journal of Computer Applications. 124, 13 ( August 2015), 1-8. DOI=10.5120/ijca2015905706
Abstract
The feature selection approach provides improved prediction and minimizes the computation time. Due to the higher numbers of features the understanding of the data in pattern recognition becomes difficult sometimes. That’s why researchers have used different feature selection techniques with the single classifiers in their intrusion detection system to build up a model which gives a better accuracy and prediction performance. In this paper, we provide a comparative analysis with the feature selection approach in WEKA machine learning tool using the J48 classifier. The research work show the comparison of the performance of single J48 classifier with filter methods. The prediction performance may differ marginally in some cases but with the removal of irrelevant features time complexity can be easily ignored and a better prediction rate is guaranteed.
References
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