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 Model for Depression Prediction during COVID-19 Pandemic Subject The topic of the resource covid-19; depression; machine learning; pandemic; Prediction Description An account of the resource Depression is an unfamous mental health disorder that has affected half the population worldwide. In December 2019, the break of the COVID-19 pandemic was first spotted in Wuhan, China, and later spread to 212 countries and territories worldwide, impacting half the population. It took a significant toll on their physical health and their mental health. Many among the population lost their loved ones, businesses, and being in quarantine for years, completely shifted to the online mode made everyone's life miserable. Many may be dealing with escalated levels of alcohol and drug use, sleeplessness, and an anxious state of mind. So, the need to address this and help the severely affected ones is significant. Self-quarantine also causes additional stress and challenges the mental health of citizens. This paper intends to identify the people who were mentally affected by the pandemic using machine learning techniques. A survey was conducted among college-going students and professionals. The paper used classification techniques such as Naive Bayes, KNN, Random Forest, Logistic Regression, k-fold cross-validation to get results. Support Vector Machine gave the maximum accuracy of 99.35%. 2022 IEEE. Creator An entity primarily responsible for making the resource Joshi S.; Ghosh A.; Shukla S. Source A related resource from which the described resource is derived IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics, ICDCECE 2022 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/ICDCECE53908.2022.9792792" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICDCECE53908.2022.9792792</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133415857&amp;doi=10.1109%2FICDCECE53908.2022.9792792&amp;partnerID=40&amp;md5=2ce25bc59ff6dae5ee3c96ce79d588c3" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133415857&amp;doi=10.1109%2fICDCECE53908.2022.9792792&amp;partnerID=40&amp;md5=2ce25bc59ff6dae5ee3c96ce79d588c3</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166548316-2 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 Joshi S., Christ University, Department of Data Science, Bangalore, India; Ghosh A., Christ University, Centre for Counselling and Health Services, Bangalore, India; Shukla S., Christ University, Department of Data Science, Bangalore, India