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 Comparison of Machine Learning Algorithms for Predicting Chronic Kidney Disease Subject The topic of the resource Chronic Kidney Disease; CKD classification; Machine learning algorithms; Random Forest; XGBoost Description An account of the resource Early detection and characterization of chronic renal disease are crucial to ensure that patients receive the best possible treatment. This study uses data mining techniques to uncover hidden information about patients. The outcomes of using the Random Forest, Multilayer Perceptron (MLP), Support Vector Machine (SVM), Decision Tree, XGBoost, LGBM Classifier, GaussianNB, KNeighbors Classifier, and XGBRF classifier have been compared. In our study, we demonstrate that Random Forest and XGBoost algorithms are more effective in classifying and predicting the severity level of chronic kidney disease 2022 IEEE. Creator An entity primarily responsible for making the resource James N.; Kaushik J. Source A related resource from which the described resource is derived 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2022, pp. 1134-1139. Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. 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/ICACITE53722.2022.9823572" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICACITE53722.2022.9823572</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135454910&amp;doi=10.1109%2FICACITE53722.2022.9823572&amp;partnerID=40&amp;md5=65ef5e0557bf4c52f52418742048c87b" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135454910&amp;doi=10.1109%2fICACITE53722.2022.9823572&amp;partnerID=40&amp;md5=65ef5e0557bf4c52f52418742048c87b</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166543789-9 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 James N., Christ (Seems to Be University), Department of Data Science, Pune, India; Kaushik J., Christ (Seems to Be University), Department of Data Science, Pune, India