A Naïve Bayesian classifier for educational qualification

Abstract

Manual classification of the individuals into different categories based on their educational qualification is a tedious task and it may vary respective to the considered scenario. This paper proposes a classification methodology utilizing the benchmark Naïve Bayesian classification algorithm for the classification of persons into different classes based on several attributes representing their educational qualification. The experimental results are appreciable indicating that the proposed classification method can be a promising one and can be applied elsewhere. The proposed method has been experimentally verified to be 90% accurate with a high kappa value thus proving its efficiency. This classification methodology can reduce the mundane manual labor and can easily assist in categorization.