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 Predicting of Credit Risk Using Machine Learning Algorithms Subject The topic of the resource Credit risk; Feature selection; Machine learning; Testing; Training Description An account of the resource Credit risk management is one of the key processes for banks and is crucial to ensuring the banks stability and success. However, due to the need for more rigid forecasting models with strong mapping abilities, credit risk prediction has become challenging for the banking industry. Therefore, this paper attempts to predict commercial banks credit risk (CR) by using various machine learning algorithms. Machine learning algorithms, namely linear regression, KNN, SVR, DT, RF, XGB, and MLP, are compared with and without feature selection and feature extraction techniques to examine their prediction capabilities. Various determinants of credit risk (features) have been extracted to predict credit risk, and these features have been used to train machine learning models. Findings revealed that the decision tree algorithm had the highest performance, with the lowest mean absolute error (MSE) value of 0.1637 and the lowest root mean squared error (RMSE) value of 0.2158. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. Creator An entity primarily responsible for making the resource Antony T.M.; Kumar B.S. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-843, pp. 99-114. Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-99-8476-3_9" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-99-8476-3_9</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85187671116&amp;doi=10.1007%2F978-981-99-8476-3_9&amp;partnerID=40&amp;md5=a1d8be2d03d7a9942928c713d50331d2" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85187671116&amp;doi=10.1007%2f978-981-99-8476-3_9&amp;partnerID=40&amp;md5=a1d8be2d03d7a9942928c713d50331d2</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-981998475-6 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 Antony T.M., School of Commerce Finance and Accountancy, CHRIST (Deemed to be University), Bengaluru, India; Kumar B.S., School of Commerce Finance and Accountancy, CHRIST (Deemed to be University), Bengaluru, India