IDENTIFYING AND RANKING THE ATTRIBUTES THAT AFFECTS EDUCATIONAL BACKGROUND OF STUDENTS WITH LEARNING DISABILITY USING WEKA TOOL

In modern era, data mining used to find the difficulty arises in the education field. Learning disability is a major problem in academic background that influences the improvement of students. The attributes that affect the performance predict the improvement of education of students with learning disability using mining tools. These attributes includes demographic, academic, financial, parental and social support. In this research work, study conducted on student with learning disability finding the factors influencing their educational outcomes among normal student. This paper predicts the learning disability of student performance using dataset reduction and attribute selection method in WEKA tool. The reduced dataset with fewer attributes provides the tool to improve the value of education. The experimental study shows the efficacy of dataset reduction algorithm with attribute selection leads to increase the performance of student with learning disability.