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 Conference Papers Conference Paper Faculty Publications- Conference Papers 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 Heart Disease Prediction Using Ensemble Voting Methods in Machine Learning Subject The topic of the resource Ensemble Classification; Heart Disease; Machine Learning; Voting Methods Description An account of the resource Heart disease is the leading cause of mortality globally according to the World Health Organization. Every year, it results in millions of mortalities and thus billions of dollars in economic damage throughout the world. Many lives can be saved if the disease is detected early and accurately. The typical methods to predict or diagnosis heart diseases require medical expertise. Such facilities and experts are relatively expensive and not very commonly available in under developed and developing countries. Recent times, much research is done on leveraging technology for the prediction as well as diagnosis of heart diseases. Machine Learning techniques have been extensively deployed as quick, inexpensive, and noninvasive ways for heart disease identification. In this work, we present a machine learning approach in detecting heart disease using a dataset that contains vital body parameters. We used seven different models and combined them with Soft-Voting and Hard-Voting ensemble approaches to improve accuracy in 7-model and various 5-model combinations. The ensemble combinations of 5 models achieved the highest test accuracy score of 94.2%. 2022 IEEE. Creator An entity primarily responsible for making the resource Cyriac S.; Sivakumar R.; Raju N.; Woon Kim Y. Source A related resource from which the described resource is derived International Conference on ICT Convergence, Vol-2022-October, pp. 1326-1331. Publisher An entity responsible for making the resource available IEEE Computer Society Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICTC55196.2022.9952655" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICTC55196.2022.9952655</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85143255902&amp;doi=10.1109%2FICTC55196.2022.9952655&amp;partnerID=40&amp;md5=83a7472826b8a86cf968ce631efcfd29" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85143255902&amp;doi=10.1109%2fICTC55196.2022.9952655&amp;partnerID=40&amp;md5=83a7472826b8a86cf968ce631efcfd29</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 21621233; ISBN: 978-166549939-2 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 Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Cyriac S., Christ (Deemed to Be University), Department of Computer Science, Bengaluru, India; Sivakumar R., Christ (Deemed to Be University), Department of Computer Science, Bengaluru, India; Raju N., Centre for Digital Innovation Christ (Deemed to Be University), Bengaluru, India; Woon Kim Y., Centre for Digital Innovation Christ (Deemed to Be University), Bengaluru, India