![]() All of this evidence demonstrates that attendance and grades have a substantial beneficial relationship using machine learning based regression analysis. The outcomes of this study demonstrated that greater performance in professional assessment tests by medical undergraduate students has a negative link with absenteeism and a positive correlation with high attendance percentage. The research examines how absenteeism affects student outcomes using administrative panel data from California to estimate the pandemic's impact. In a Finnish University, the research examines the relationship between attendance and performance using the clustering method. Similarly, Narula and Nagar's research demonstrates a high link between attendance and grades using machine learning methods. The regression model revealed a robust link between semester GPA and attendance %, as well as overall GPA. On the basis of test score and classroom attendance data over two years, regression analysis is introduced, and correlation curves between test score and classroom attendance are plotted. Zhang and Wang's research reveals that a positive correlation exists between the desired variables using a linear regression model. The study looks into the link between students' attendance in class and their total marks in a variety of computer science programmes. According to Ahmat and Zahari's research, there is a negative relationship between absenteeism and grades, implying that more absence equals a lower grade. Various studies have shown that successful students have a better attendance record as well as a higher grade. ![]() A student's grade is determined by his/her attendance. It has been observed via different studies and blind observation that students who do not attend classes receive worse grades, but individuals who have a greater attendance rate than their peers receive higher grades. Absenteeism is described as the habit of failing to show up for class or an event without a valid justification, and the term absentee is used to characterize someone who does this regularly. At the present time India also facing these type student absentees’ problems. I In today's technologically advanced world, a major difficulty in primary and middle schools, intermediate colleges, post graduate colleges and university is the rising tendency of student absenteeism. Keywords: Linear Regression model, Machine Learning, Descriptive Statistical Analysis, Statistical Analysis. This study will benefit both the college administration and the students by raising awareness of the disadvantages of not attending classes. ![]() To investigate the impact of class absentees on student score, a regression model was created. The study also discovered that absenteeism from class had a negative link with the score (r=-0.6088). According to the results of this study, there are considerable variations between absentees and score (t-test=-4.06075,p<0.05). The descriptive, student's t-test, Pearson correlation, and regression models were used in this study's statistical analysis. ![]() Linear regression analysis is one of excellent method of machine learning. This research is focuses on absentees of student in class and score and has been carried out by using linear regression analysis. Absenteeism from classrooms amongst students is an international problem that does not only affect Indian students.
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