Year: 2016
Type: article
Abstract: At the present time, the amount of data in educational database is increasing day by day.These data enclose the concealed information that can lift the student's performance.Among all classification algorithms, decision tree is most algorithm.Decision tree provides the more correct and relevant results which can be beneficial in improvement of learning outcomes of a student.The ID3, C4.5 and CART decision tree algorithms are already implemented on the data of students to anticipate their accomplishment.All three classification algorithm have a limitation that they all are used only for small So, for large database we are using a new algorithm i.e.SPRINT which removes all the memory restriction and accuracy arrives in other algorithms.It is fast and scalable than others because it can be implemented in both serial and parallel fashion good data replacement and load balancing.In this paper, we are representing a new SPRINT decision tree algorithm which will used to solve the problems of classification in educational data system.
Author: Nitya Upadhyay
Language: English
Subfield: Computer Science Applications
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: bronze
OpenAlex ID: W4248369867