学生成绩分析系统采用累积预测算法

J. Rose, K. Vijayakumar, S. Sakthivel
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引用次数: 23

摘要

越来越多的人倾向于用自动化来完成平凡的任务,对已经具备良好编程技能的学生的期望也在上升。与此同时,越来越多的学生发现很难获得获得他们梦寐以求的it工作所需的技能。该项目的目的是通过在大学水平上使用SPAS来弥合雇主和公司未来员工之间的差距。学生表现分析系统(SPAS)是一个在线网络应用系统,它使学生能够事先知道他们的技能水平是否足以在必要的输入下被安置。SPAS有一个智能学习算法,利用丰富的数据库,分析以前学生的特征记录,并开发一个模型,以进一步预测。SPAS对学生的成绩评价是通过累积预测算法,该算法涉及在可用数据上生成几棵随机森林树。随着数据可用性的增加,SPAS学习并创建其模型以达到更高的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Students' performance analysis system using cumulative predictor algorithm
Towards automation to do mundane tasks and the expectations for students already equipped with good programming skills is on the rise. In parallel, there has been a rising number of students who find it difficult to attain the skills necessary in order to get the dream IT job they desire. The aim of this project is to bridge the gap between the employer and the future employee of the company by the use of SPAS at college level. Student performance analysis system (SPAS) is an online web application system which enables students to know prior hand if their level of skills for the placement is enough to get placed or not, given the necessary inputs. SPAS has an intelligent learning algorithm which utilises a rich database, analyses the records of previous students' traits and develops a model for further prediction. The performance evaluation of students by SPAS is by the cumulative predictor algorithm involving generation of several random forest trees on the available data. SPAS learns and creates its model reaching higher accuracy with increasing data availability.
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