… better performance than the CHAID algorithm which is 65.00%. … both algorithms to produce
rules in one class for liver disease. … algorithms are capable to produce rules for liver disease. …

… fatal disease in many countries like – Egypt, Moldava etc. For this research paper, the main
aim is to predict liver disease using different classification algorithms. The algorithms used …

… to find the best classification algorithm in terms of precision, … classification algorithms
namely, Naive Bayes classification (NBC), Bagging algorithm, KStar algorithm, Logistic algorithm …

… Automatic classification tools may reduce burden on doctors. This paper … classification
algorithms for the classification of some liver patient datasets. The classification algorithms …

… doctors to diagnose the disease within a short duration … classification algorithms and compare
their predictive accuracies so as to find the best classifier for determining the liver disease. …

… of classification model for liver diagnoses by using different classification algorithms that
have … In this study, several classification algorithms that have not been tested before on BUPA …

… models, one can check for the occurrence or absence of liver disease. In this paper, five
classification algorithms [2] were measured to compare their performance based on data of liver …

… diffuse liver disease tissue classification. In this paper, we present a detailed description of
the algorithms … Our main goal is to investigate the use of well-known quantitative classification …

… Machine Learning Algorithms Supervised learning algorithms were employed in this
investigation to classify the liver tissues into fatty and normal using the same data set that was used …

… such as classification, clustering, association rules and so on. The main objective of this
research work is to predict liver diseases using classification algorithms. The algorithms used in …