Determining Dominant Factor for Students Performance Prediction by Using Data Mining Classification Algorithms
Year: 2015
Type: article
Abstract: The central problem in the process of a discovering knowledge from data, in the field of educational data mining, is to identify a representative set of data, on whose basis a classification model will be constructed.This paper presents the research results in reduction of data dimensionality, in the classification problems of prediction of student's performances on the example from high schools, in Canton Tuzla.In this paper are shown different algorithms that are used to reduce the dimensionality of data and to development of a data mining model for predictions of performances of students, on the basis of their personal demographic and societal features.It was found that algorithms Random Forest and J48 generate classification model with and accuracy higher than 71%.
Authors: Osmanbegović, Edin, Suljić, Mirza, Agić, Hariz
Language: English
Subfield: Computer Science Applications
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W2784718541