Paper Title
A Comparative Accuracy Prediction of Liver Disease Using Machine Learning Techniques

Abstract
The viability of people suffering from liver disease isone of the main concerns of the human living. Therefore preliminary detection of liver disease is essential for better treatment. Early prediction of disease by sophisticated symptoms is very difficult for practitioners. For many, the signs become apparent when its too late. Current work aims to combat this epidemic by using machine learning techniques to broaden our understanding of the nature of liver disease. The main goal of this work is focused on a algorithm for classifying healthy individuals in a liver data set. Based on their success factors, this study intent to differentiate classification algorithms and provide outcomes of accurate results. Keywords - Liver disease, Comparison, Accuracy, SVM, K- MEANS, KNN, (ML algorithms), Prediction