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Backlog Prediction using Classification Techniques of Machine Learning
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 182 - Number 23 |
| Year of Publication: 2018 |
| Authors: Aditi Parikh, Neelam Chaplot, Mukesh Agarwal |
10.5120/ijca2018918020
|
Aditi Parikh, Neelam Chaplot, Mukesh Agarwal . Backlog Prediction using Classification Techniques of Machine Learning. International Journal of Computer Applications. 182, 23 ( Oct 2018), 6-9. DOI=10.5120/ijca2018918020
Abstract
Every Educational organization’s success rate depends highly on the success of the student. Many types of research are taking place in education field using machine learning techniques. Machine Learning has the ability to learn about the student and predict the performance of the student. In this research, analysis has been done to predict the possibility of the student getting backlog using various attributes related to the student and applying machine learning algorithms. Data of 648 students were collected containing 30 attributes. Preprocessing steps were adopted to convert the data in usable form. Once the data was ready then the Random Forest method was applied as learning algorithm. The accuracy of the random forest method was 94%. This type of analysis can help educational institutes take preventive measures for the improvement and monitoring of the student
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