IDENTIFYING AND RANKING THE ATTRIBUTES THAT AFFECTS EDUCATIONAL BACKGROUND OF STUDENTS WITH LEARNING DISABILITY USING WEKA TOOL
Main Article Content
Abstract
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.
Downloads
Download data is not yet available.
Article Details
Section
Articles
COPYRIGHT
Submission of a manuscript implies: that the work described has not been published before, that it is not under consideration for publication elsewhere; that if and when the manuscript is accepted for publication, the authors agree to automatic transfer of the copyright to the publisher.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work
- The journal allows the author(s) to retain publishing rights without restrictions.
- The journal allows the author(s) to hold the copyright without restrictions.