Introspecting the Happiness amongst University Students using Machine Learning

التفاصيل البيبلوغرافية
العنوان: Introspecting the Happiness amongst University Students using Machine Learning
المؤلفون: Ranjan, Sakshi, Priyadarshini, Pooja, Mishra, Subhankar
سنة النشر: 2023
المجموعة: Computer Science
مصطلحات موضوعية: Computer Science - Computers and Society
الوصف: Happiness underlines the intuitive constructs of a specified population based on positive psychological outcomes. It is the cornerstone of the cognitive skills and exploring university student's happiness has been the essence of the researchers lately. In this study, we have analyzed the university student's happiness and its facets using statistical distribution charts; designing research questions. Furthermore, regression analysis, machine learning, and clustering algorithms were applied on the world happiness dataset and university student's dataset for training and testing respectively. Philosophy was the happiest department while Sociology the saddest; average happiness score being 2.8 and 2.44 respectively. Pearson coefficient of correlation was 0.74 for Health. Predicted happiness score was 5.2 and the goodness of model fit was 51%. train and test error being 0.52, 0.47 respectively. On a Confidence Interval(CI) of 5% p-value was least for Campus Environment(CE) and University Reputation(UR) and maximum for Extra-curricular Activities(ECA) and Work Balance(WB) (i.e. 0.184 and 0.228 respectively). RF with Clustering got the highest accuracy(89%) and F score(0.98) and the least error(17.91%), hence turned out to be best for our study
Comment: 5 Figures, 10 tables, 12 pages. Accepted at Happiness Meet IIT Kharagpur-2022
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2312.10092
رقم الأكسشن: edsarx.2312.10092
قاعدة البيانات: arXiv