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Research Journal of Pharmacy and Technology
Year : 2019, Volume : 12, Issue : 8
First page : ( 3720) Last page : ( 3725)
Print ISSN : 0974-3618. Online ISSN : 0974-360X.
Article DOI : 10.5958/0974-360X.2019.00636.X

Hepatitis-Infectious Disease Prediction using Classification Algorithms

Kumar N Komal1,*, Vigneswari D2

1Department of Computer Science and Engineering, St. Peter's Institute of Higher Education and Research, Avadi, Chennai, India

2Department of Information Technology, KCG College of Technology, Karapakkam, Chennai, India

*Corresponding Author E-mail: komalkumarnapa@gmail.com

Online published on 24 December, 2019.

Abstract

Classification algorithms play a substantial role in analyzing and predicting infectious diseases. Hepatitis is a provocative condition of the liver tissues by developing a yellow tarnishing effect in the skin, the condition of hepatitis can be acute or chronic depending on the severity. This paper aims at comparing the performance of the classifiers in analyzing and predicting the infectious hepatitis disease. Logistic regression, random forest, decision tree, C4.5 and Multilayer perceptron classifiers are used in this analysis for prediction; the performance comparison metric is based on the TPR and accuracy values. In this performance comparison of predicting infectious hepatitis disease, Random forest classifier has achieved a higher accuracy of 90.3226% in correctly classifying the instances with an execution time of 0.14 sec than the other classifiers under analysis.

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Keywords

C4.5, Classifiers, Decision tree, Hepatitis, Regression.

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