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 Machine Learning Based Recession Prediction Analysis Using Gross Domestic Product (GDP) Subject The topic of the resource Covid-19; Economical Statistics; Gross Domestic Product; Machine Learning; Random Forest; Recession Description An account of the resource This research article aims to explore the prediction and analysis of recessions, with a particular focus on Gross Domestic Product (GDP). The study examines the impact of recessions on different countries, namely India, USA, Germany, China, and Bangladesh, while also considering the influence of the COVID-19 pandemic on these nations in relation to the recessionary effects. Furthermore, the study lists many machine learning techniques that could be used to anticipate recessions. This research mainly focuses on predicting recession using different machine learning models. The research not only provides an in-depth analysis of the recessionary impacts on different economies but also serves as a foundation for future implementation of these algorithms for accurate recession prediction and proactive economic decision-making. This research study mainly focuses on machine learning algorithms like Random Forest, Support Vector Machines and Regression Model. The GDP prediction comparison is taking last twenty years data. This is mainly compared before and after COVID-19 situation. 2023 IEEE. Creator An entity primarily responsible for making the resource Haritha T.H.; Joby A.; Javapandian N. Source A related resource from which the described resource is derived 7th International Conference on Electronics, Communication and Aerospace Technology, ICECA 2023 - Proceedings, pp. 492-498. 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 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICECA58529.2023.10394958" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICECA58529.2023.10394958</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85186127859&amp;doi=10.1109%2FICECA58529.2023.10394958&amp;partnerID=40&amp;md5=95694b94d6b3e6f157bce4efb01c1581" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85186127859&amp;doi=10.1109%2fICECA58529.2023.10394958&amp;partnerID=40&amp;md5=95694b94d6b3e6f157bce4efb01c1581</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835034060-0 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 Haritha T.H., CHRIST (Deemed to Be University), Department of CSE, India; Joby A., CHRIST (Deemed to Be University), Department of CSE, India; Javapandian N., CHRIST (Deemed to Be University), Department of CSE, India