2nd International Conference on Fostering Interdisciplinary Research In Health Sciences (ICFIRHS) 2019 (01-May-2019)        |

Journal :   Research Journal of Pharmacy and Technology

Volume No. :   12

Issue No. :  8

Year :  2019

Pages :   3720-3725

ISSN Print :  0974-3618

ISSN Online :  0974-360X


Allready Registrered
Click to Login

Hepatitis- Infectious Disease Prediction using Classification Algorithms

Address:   N Komal Kumar1*, D Vigneswari2
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
DOI No: 10.5958/0974-360X.2019.00636.X

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.
C4.5, Classifiers, Decision tree, Hepatitis, Regression.
N Komal Kumar, D Vigneswari. Hepatitis- Infectious Disease Prediction using Classification Algorithms. Research J. Pharm. and Tech 2019; 12(8): 3720-3725.
[View HTML]     

Visitor's No. :   610961