• M Kavitha
• Dr S Subbaiah

Chronic Disease Prediction shows a fundamental role in healthcare informatics. It is vital to identify the disease at an initial stage. This paper describes a survey on the utilization of feature selection and classification techniques for the diagnosis and prediction of chronic diseases. Adequate selection of features showsanimportantpart for improvingprecision of classification systems. Dimensionality reduction supports in refining overall performance of machine learning algorithm. In this paper, we present a completesummary of various feature selection methods and their inherent pros and cons.

Feature Selection, Chronic Disease Prediction, Wrapper Method, Filter Method, Embedded Method.

"A STUDY ON FEATURE SELECTION FOR CHRONIC DISEASE PREDICTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.351-356, March-2019, Available :http://www.jetir.org/papers/JETIRAQ06072.pdf

"A STUDY ON FEATURE SELECTION FOR CHRONIC DISEASE PREDICTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 3, page no. pp351-356, March-2019, Available at : http://www.jetir.org/papers/JETIRAQ06072.pdf