Estimating the Surveillance of Liver Disorder using Classification Algorithms

International Journal of Computer Applications (0975 – 8887) Volume 57– No.6, November 2012

4 Pages Posted: 15 Jan 2020

See all articles by Dr. A. S. Aneeshkumar

Dr. A. S. Aneeshkumar

AJK College of Arts and Science; Alpha Arts and Science College; IRDP Group of Journals

C Jothi Venkateswaran

Presidency College

Date Written: November 10, 2012

Abstract

Data mining is an activity of extracting some useful knowledge from a large data base, by using any of its techniques. In this paper we are using classification, one of the major data mining models, which is used to predict previously unknown class of objects. Unlike other diseases, liver disorder prediction from common symptoms is typically difficult job for medical practitioners. Most of the features or symptoms are seen in many other fever related diseases and so it is not free from false assumptions. In most cases the opportunity of liver disease will not identified because of the domination of other diseases.

Keywords: Data mining, Classification, Liver Disease, Preprocessing, Naive Bayesian, C4.5 decision tree

Suggested Citation

Aneeshkumar, Dr. A. S. and Aneeshkumar, Dr. A. S. and Venkateswaran, C Jothi, Estimating the Surveillance of Liver Disorder using Classification Algorithms (November 10, 2012). International Journal of Computer Applications (0975 – 8887) Volume 57– No.6, November 2012, Available at SSRN: https://ssrn.com/abstract=3509372

Dr. A. S. Aneeshkumar (Contact Author)

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C Jothi Venkateswaran

Presidency College ( email )

Chennai
India

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