• Tanneeru Rachana
• Somu LeelaMadhav
• Mr.Rajkumar

Patients with liver disease have been continuously increasing because of excessive consumption of alcohol, inhale of harmful gases, intake of contaminated food, pickles and drugs.Liver patient datasets are investigated for building classification models in order to predict liver disease. This dataset was used to evaluate prediction algorithms in an effort to reduce burden on doctors.Chronic liver disease refers to disease of the liver which lasts over a period of six months.So in that, we will take results of how much percentage patients get disease as a positive information and negative information.Using classifiers, we are processing liver disease percentage and values are shown in a confusion matrix. We proposed a various classification scheme which can effectively improve the classification performance in the situation that training dataset is available.

liver disease,confusion matrix,ROC-AUC.

"Accuracy Prediction and Classification Using Machine Learning Techniques for Liver Disease ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 7, page no.b460-b463, July-2021, Available :http://www.jetir.org/papers/JETIR2107186.pdf

"Accuracy Prediction and Classification Using Machine Learning Techniques for Liver Disease ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 7, page no. ppb460-b463, July-2021, Available at : http://www.jetir.org/papers/JETIR2107186.pdf