Undergraduate engineering students employment prediction using hybrid approach in machine learning

The knowledge discovery from student’s data can be very useful in predicting the employment under different categories. machine learning is helping this regard up to great extent. In paper, a hybrid model of has proposed predict jobs categories, students may get their campus placement. considered groups are undergraduate courses engineering stream having semester’s scheme academic. mapping predicted based on previous seven semesters marks as well personality index. consists three multilayer feed forward architecture, radial basis function neural network and K-means clustering method. provided relative chances available each job category with high accuracy consistency.