SIGNIFICANCE OF INFORMATION GAIN RATIO FOR IMPROVING CLASSIFICATION OF HEART DISEASES

Authors

  • R.KARTHIKEYAN Assistant Professor, Department of Computer Science and Engineering. Bharath University, Selaiyur, Chennai-600073, India
  • A.KUMARAVEL Professor and Dean, Department of Computer Science and Engineering. Bharath University, Selaiyur, Chennai-600073, India
  • V.KHANAA Professor, and Dean Department of Information Techonology. Bharath University, Selaiyur

Keywords:

Heart disease data set, Information gain, Decision trees, Decision rules, Meta classifiers, Bayes classifiers, Function classifiers.

Abstract

Mechanizing the prediction of new patients’ heart disease diagnosis based on data mining on historical data is an extremely useful tool in the cardiology stream. There exist many studies focusing on this specific aspect of the filtering the attributes. The objective of this research paper is two-fold. First, we look into four distinct classifiers for evaluating the relevancy of the attributes and we investigate the effects of feature selection in such experiments.

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Published

30.06.2015

How to Cite

R.KARTHIKEYAN, A.KUMARAVEL, & V.KHANAA. (2015). SIGNIFICANCE OF INFORMATION GAIN RATIO FOR IMPROVING CLASSIFICATION OF HEART DISEASES. International Journal of Pharma and Bio Sciences, 6(2), 182–190. Retrieved from https://ijpbs.net/index.php/journal/article/view/4215

Issue

Volume 6, Issue 2, 2015

Section

Research Articles

Categories

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