Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Performance evaluation of random forest with feature selection methods in prediction of diabetes Subject The topic of the resource Classification accuracy; Data mining; Feature selection method; Percentage split; Random forest Description An account of the resource Data mining is nothing but the process of viewing data in different angle and compiling it into appropriate information. Recent improvements in the area of data mining and machine learning have empowered the research in biomedical field to improve the condition of general health care. Since the wrong classification may lead to poor prediction, there is a need to perform the better classification which further improves the prediction rate of the medical datasets. When medical data mining is applied on the medical datasets the important and difficult challenges are the classification and prediction. In this proposed work we evaluate the PIMA Indian Diabtes data set of UCI repository using machine learning algorithm like Random Forest along with feature selection methods such as forward selection and backward elimination based on entropy evaluation method using percentage split as test option. The experiment was conducted using R studio platform and we achieved classification accuracy of 84.1%. From results we can say that Random Forest predicts diabetes better than other techniques with less number of attributes so that one can avoid least important test for identifying diabetes. Copyright 2020 Institute of Advanced Engineering and Science. All rights reserved. Creator An entity primarily responsible for making the resource Raghavendra S.; Santosh Kumar J. Source A related resource from which the described resource is derived International Journal of Electrical and Computer Engineering, Vol-10, No. 1, pp. 353-359. Publisher An entity responsible for making the resource available Institute of Advanced Engineering and Science Date A point or period of time associated with an event in the lifecycle of the resource 2020-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.11591/ijece.v10i1.pp353-359" target="_blank" rel="noreferrer noopener">https://doi.org/10.11591/ijece.v10i1.pp353-359</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85073363164&amp;doi=10.11591%2Fijece.v10i1.pp353-359&amp;partnerID=40&amp;md5=bbbe979964eaf91d3b7e7eded475f799" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85073363164&amp;doi=10.11591%2fijece.v10i1.pp353-359&amp;partnerID=40&amp;md5=bbbe979964eaf91d3b7e7eded475f799</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access; Green Open Access Relation A related resource ISSN: 20888708 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Raghavendra S., Department of Computer Science and Engineering, CHRIST Deemed To Be University, Kanmanike, Kumbalgodu, Mysore Road, Bangalore, 560074, India; Santosh Kumar J., Department of Computer Science and Engineering, KSSEM, India