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 Linear Regression Tree and Homogenized Attention Recurrent Neural Network for Online Training Classification Subject The topic of the resource Decision Tree; Feature Selection; Homogenized Attention; Information Technology; Linear Regression; Recurrent Neural Network; Sentiment Analysis Description An account of the resource Internet has become a vital part in people's life with the swift development of Information Technology (IT). Predominantly the customers share their opinions concerning numerous entities like, products, services on numerous platforms. These platforms comprises of valuable information concerning different types of domains ranging from commercial to political and social applications. Analysis of this immeasurable amount of data is both laborious and cumbersome to manipulate manually. In this work, a method called, Linear Regression Tree-based Homogenized Attention Recurrent Neural Network (LRT-HRNN) for online training is proposed. In the first step, a dataset consisting of student's reactions on E-learning is provided as input. A Linear Regression Decision Tree (LRT) - based feature (i.e., student's reactions and posts) selection model is applied in the second step. The feature selection model initially selects the commonly dispensed features. In the last step, HRNN sentiment analysis is employed for aggregating characterizations from prior and succeeding posts based on student's reactions for online training. During the experimentation process, LRT-HRNN method when compared with existing methods such as Attention Emotion-enhanced Convolutional Long Short Term Memory (AEC-LSTM) and Adaptive Particle Swarm Optimization based Long Short Term Memory (APSO-LSTM, performed better in terms of accuracy(increased by 6%), false positive rate (decreased by 22%), true positive rate (increased by 7%) and computational time (reduced by 21%). 2022 IEEE. Creator An entity primarily responsible for making the resource Yadhunandan A.K.K.; Arun Kokatnoor S. Source A related resource from which the described resource is derived International Conference on Trends in Electrical, Electronics, Computer Engineering, TEECCON 2022, pp. 78-83. 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/TEECCON54414.2022.9854833" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/TEECCON54414.2022.9854833</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85138106958&amp;doi=10.1109%2FTEECCON54414.2022.9854833&amp;partnerID=40&amp;md5=53b6f80c4e6c758ab95b203d43cde624" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85138106958&amp;doi=10.1109%2fTEECCON54414.2022.9854833&amp;partnerID=40&amp;md5=53b6f80c4e6c758ab95b203d43cde624</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166548366-7 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 Yadhunandan A.K.K., Christ (Deemed to Be University), School of Engineering and Technology, Department of Computer Science and Engineering, Bangalore, 560074, India; Arun Kokatnoor S., Christ (Deemed to Be University), School of Engineering and Technology, Department of Computer Science and Engineering, Bangalore, 560074, India