In recent days there is increase in deaths due to liver disorder problems. Liver is the largest internal organ and gland in human body. The liver functions involve in Digestion, Metabolism, Immunity and supply nutrients in the body. projection of liver disorders at starting stages can lower the risks and diagnosis at early stage can definitely heal. the main concern of this project is to design and develop a medical diagnosis expert system which helps the physicians in decision making through collected data of liver disorders by using understanding criterions. classification algorithms like Decision Trees(J48), Naive Bayes, Random Forest and Multilayer Perceptron are used to sort and contrast the success and rate of correction of the data. It helps in implementation of classification models in terms of correctness and reduce the evaluation time is required to develop models that can grasp faster with better conception of models. a comparative investigations of data classification precision using data of liver disorders are represented. Comparisons based on performances between classifier algorithms is considered quantitatively.
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