Quality analysis of graduates from Chiang Mai University using machine learning methods

Abstract

This research aims to measure the quality of Chiang Mai University graduates, construct the model which can predict income accurately and find the variables effected to Chiang Mai University graduates' quality. Through data collection and integration, we got the students' data in Chiang Mai University from academic year 2012-2014. Then we brought in data and used three machine learning models (artificial neural networks, logistic regression, and support vector machines) to perform multiple classifications. All three have relatively good prediction results with good accuracy. The results show us that the income of graduates of Chiang Mai University is normally distributed. Most of the graduates have a medium income, and a small number of people earn high and low incomes. The best way to increase income for students who have just entered university is to improve their English scores and choose medical-related majors. For senior students, choosing to study for a higher degree and maintaining a high GPA is a very effective way to increase their income.