(untitled) (International Journal of Engineering and Computer Science, 2017)
In the recent years, data mining is the most important domain in the real world aspects. By using data mining Techniques, we can identify the knowledge of different areas and get the best patterns. Educational institutions and universities are facing problems in terms of student employability. It became a big task for the educational institutions. In this regard, we identified the techniques to bring co-relation between the student academics and faculty responsibilities, where co-relation pattern means reading the knowledge from the educational student performance data. Using this data, we are applying different Data mining Techniques to find out the useful patterns and fill the gap between the Student Academics and Employability. This paper includes survey on different prediction algorithms like Classification, decision tree algorithm, C4.5, Feature with Graph structure, Bayesian, RIPPER, SVM, and compares the best performances on different aspects.