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 Application of Regression Analysis of Student Failure Rate Subject The topic of the resource Machine learning; Regression; Student failure Description An account of the resource The education sector has been rapidly growing and is currently facing several challenges. One such challenge is identifying students who are at risk of failing, as this can help educators provide targeted interventions to improve student performance. Machine learning models have been developed to predict the probability of student failure based on various student performance metrics to address this issue. In this paper, we present a regression-based model that predicts the probability of student failure using student performance metrics such as attendance, previous academic performance, and demographic information. The model was trained on a dataset of students and achieved high accuracy in predicting the probability of student failure. While the model performs well in predicting the probability of student failure, there is always room for improvement. Possible enhancements to the model include feature engineering, ensemble learning, hyperparameter tuning, deep learning, and interpretability. These enhancements can improve the models accuracy, stability, and transparency, leading to better predictions and targeted interventions for at-risk students. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. Creator An entity primarily responsible for making the resource Sybol S.S.; Srivasatava S.; Sharma S. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-994 LNNS, pp. 897-910. 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/10.1007/978-981-97-3180-0_60" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-97-3180-0_60</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200688709&amp;doi=10.1007%2F978-981-97-3180-0_60&amp;partnerID=40&amp;md5=d269e62e262b31349558f23eba348da6" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200688709&amp;doi=10.1007%2f978-981-97-3180-0_60&amp;partnerID=40&amp;md5=d269e62e262b31349558f23eba348da6</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-981973179-4 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 Sybol S.S., CHRIST (Deemed to be University), Delhi NCR, India; Srivasatava S., CHRIST (Deemed to be University), Delhi NCR, India; Sharma S., Uttaranchal University, Dehradun, India