As the computer technology and computer network technology are developing, the amount
of data in information industry is getting higher and higher. It is necessary to analyze this …

Although data mining has been successfully implemented in the business world for some
time now, its use in higher education is still relatively new, ie its use is intended for …

The ensemble approach such as boosting is based on heuristic system to develop
prediction paradigms. The ensemble learning techniques are typically more accurate than …

At the present time, the amount of data stored in educational database is increasing swiftly.
These databases contain hidden information for improvement of student's performance …

Predicting the student performance is playing vital role in educational sector so that the
analysis of student's status helps to improve for better performance. Applying data mining …

The large amounts of data used nowadays have motivated research and development in
different disciplines in order to extract useful information with a view to analyzing it to solve …

Growth of an educational institute can be measured in terms of successful students of the
institute. The analysis related to the prediction of students academic performance in higher …

Student's performance prediction is essential to be conducted for a university to prevent
student fail. Number of student drop out is one of parameter that can be used to measure …

As students' behaviors are important factors that can reflect their learning styles and living
habits on campus, extracting useful features of them plays a helpful role in understanding …

Context Recent studies have established the fact that the supply of handy and successful
software has decreased to 6%. The past studies have also attributed this supply failure to …