Genetic Algorithm based CFS and Naive Bayes Algorithm to Enhance the Predictive Accuracy

T  Karthikeyan  and P  Thangaraju

doi:10.17485/ijst/2015/v8i27/53086

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Genetic Algorithm based CFS and Naive Bayes Algorithm to Enhance the Predictive Accuracy

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Indian Journal of Science and Technology

DOI: 10.17485/ijst/2015/v8i27/53086

Year: 2015, Volume: 8, Issue: 26, Pages: 1-8

Original Article

Genetic Algorithm based CFS and Naive Bayes Algorithm to Enhance the Predictive Accuracy

T. Karthikeyan¹ and P. Thangaraju^2*

¹Department of Computer Science, PSG College of Arts and Science, Coimbatore – 641014, Tamil Nadu, India
² Department of Computer Applications, Bishop Heber College, Tiruchirappalli – 620017, Tamil Nadu, India; [email protected]

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

For better classification accuracy in the area of data mining, feature selection techniques are applied to medical data sets. In this work genetic algorithm and Particle Swarm Optimization search techniques and correlation based feature selection is used for evaluation and naive bayes classifier for classification purpose. The hepatitis data set, taken from the UCI machine learning repository, is applied in this work. Accuracy and time is the outcome of the classification model and also various measures like sensitivity, specificity, precision and recall are also calculated.
Keywords: Correlation based Feature Selection, Data Mining, Feature Selection, Genetic Algorithm, Naive Bayes Algorithm, Particle Swarm Optimization