Published Paper Details:

Dropout rates for students are increasing. We need to make certain measurements to find out the factors which are leading to the dropout of the student by using machine learning techniques with which we can choose an alternate way to select the dropout rates of the student from the course. We can make an analysis of each and every student by identifying the most related features. There are many factors which are responsible for the dropouts of the students like financial, economic, and many other problems. If the dropout rate of the students is increasing then the employment opportunities of the students will decrease gradually. Here we are going to implement some of the Machine Learning techniques to identify the students who are likely to drop out. Our main task is to apply different machine learning techniques to the selected features. A comparison is made for machine learning algorithms with each metric, and the model that gives the more appropriate result is considered the best one.