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 Analysis of Multinomial Classification for Legal Document Categorization Subject The topic of the resource Legal document classification; Machine learning; Natural language processing Description An account of the resource A major area of research today is the application of Machine Learning Techniques for Document or Text Classification. Document Classification is an important aspect of Electronic Discovery in the Legal domain. The need for the process to be automated has been realized over the past few years. Multinomial Classification is a well-known Supervised Machine Learning Technique that helps us classify if there are more than two classes used for the purpose of Classification. Evaluation metrics such as Precision, Recall, and F1 Score have been used to measure the efficiency of Classification. Logistic Regression and Gradient Boosting Algorithms have outperformed other Multiclass Classification techniques. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. Creator An entity primarily responsible for making the resource Joseph T.; Adiyillam V. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-922 LNNS, pp. 177-183. 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/10.1007/978-981-97-0975-5_15" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-97-0975-5_15</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85197313171&amp;doi=10.1007%2F978-981-97-0975-5_15&amp;partnerID=40&amp;md5=74b587d74622113ec5714198daf0c3f7" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85197313171&amp;doi=10.1007%2f978-981-97-0975-5_15&amp;partnerID=40&amp;md5=74b587d74622113ec5714198daf0c3f7</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-981970974-8 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 Joseph T., Research Scholar, Department of Computer Science, CHRIST (Deemed to Be University), Bengaluru, 560029, India; Adiyillam V., Department of Statistics and Data Science, CHRIST (Deemed to Be University), Bengaluru, 560029, India