Categorization of Liver Disease Using Classification Techniques
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2017, Vol 5, Issue 5
Abstract
Health is an important issue in human life and facing various diseases by most of the people. Liver Diseases is very serious liver facing by most of the human being. Machine learning techniques are very effective tool through we classify the liver and non-liver patients with better accuracy. Classification is one of the easy and effective technique through which we get better accuracy to judge liver data. In this paper we use C4.5, Random Forest, CART, Random Tree and REP tree classification method and get better accuracy to detect liver disease. We achieved better accuracy 79.22% in Random Forest using 80-20% training-testing data partition.
Authors and Affiliations
Ashwani Kumar, Neelam Sahu
Keywords
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