  Educational Data Mining (EDM) is a promising field, where data mining is
widely used for predicting students performance. One of the most prevalent and
recent challenge that higher education faces today is making students
skillfully employable. Institutions possess large volume of data; still they
are unable to reveal knowledge and guide their students. Data in education is
generally very large, multidimensional and unbalanced in nature. Process of
extracting knowledge from such data has its own set of problems and is a very
complicated task. In this paper, Engineering and MCA (Masters in Computer
Applications) students data is collected from various universities and
institutes pan India. The dataset is large, unbalanced and multidimensional in
nature. A cluster based model is presented in this paper, which, when applied
at preprocessing stage helps in parsimonious selection of variables and
improves the performance of predictive algorithms. Hence, facilitate in better
prediction of Students Employability.
