Paper Title: A Machine Learning Approach to Identify the Correlation and Association among the Students’ Educational Behavior
Education is known as the backbone of a nation. So, a nation must be concern about its people and their education system. In the modern era, most of the early age students are not abling to concentrate on their study due to various factors surrounding them. In this study, we have tried to find out the most significant factors harmful for a student. We have also tried to observe the correlation among the factors. These findings may help students and their parents to know about their daily activities which are restricting them to do better in their study. For performing this study, we have collected information and built a dataset which contains 1000 instances where each instance has 32 unique attributes. We have used Machine Learning techniques for processing the dataset as well as selecting the significant attributes. Moreover, we have used Association Rule Mining technique for finding out the most correlated features of the dataset. We have used Apriori algorithm for implementing Association Rule Mining and we found 4 rules.