HAPPINESS IN METHOD OF LEARNING PREDICTOR WITH FUSION OF VARIOUS ML ALGORITHMS IN POST COVID SITUATION SCHOOL BOARD EXAM STUDENTS

Abstract

Covid 19's youngsters are feeling insecure and uneasy during the Pandemic. The most serious source of concern is that, due to the Corona outbreak, students were compelled to attend their classes online and then take their board examinations in person. Use machine learning models to collect data from students once a week to boost student happiness. The youngsters will report information regarding their whereabouts, smartphone usage, and behavioural responses once a week. The model can tell the difference between students who are happy and those who are sad. Depressed students are given extra attention to help them cope with the exam. We looked at a few different machine learning models and discovered that the average categorization accuracy is around 80%.