Classification is the most commonly applied machine learning technique that classifies large population of records based on the training set and the feature values. The important task of a classifier is to predict categorical class labels and construct a model for the target class. The classification techniques are widely used in the emerging research fields of bioinformatics. Prediction of disease that is chronic in nature is a big challenge for medical experts. Thus, in the field of bioinformatics, it is vital to predicting the disease accurately that will help the physicians to begin the treatment process. This work develops a chronic disease prediction model by implementing various machine learning classification techniques. The model analyzes the data from the data set and results in the prediction accuracy in each case of the classifier.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.