基于随机森林算法的学生成绩预测的实现
Realization of Student Grade Prediction Based on the Random Forest Algorithm
钱涛1
作者信息
- 1. 浙江农业商贸职业学院 浙江绍兴 312088
- 折叠
摘要
教育数据挖掘是数据挖掘中的重要领域之一,其中成绩预测是研究的重点内容,成绩数据是学生学习行为的重要反映.基于数据挖掘技术,通过采集学生的基本信息、图书借阅、消费行为、门禁数据等各类数据,挖掘行为特征与学习成绩之间的关联性,构建基于学生行为数据的成绩预测模型.以实现对学生异常情况的早期预警,优化教学实施过程,有利于学校对不同类群学生进行培养、引导和管理.
Abstract
Educational data mining is one of the important fields in data mining,and grade prediction is its key re-search content.Grade data is an important reflection of students'learning behavior.Based on data mining technol-ogy,this paper explores the correlation between behavioral characteristics and academic performance by collecting various data such as students'basic information,book borrowing,consumption behavior and access control data,and builds a grade prediction model based on student behavior data,in order to achieve the early warning of the ab-normal situation of students,optimize the teaching implementation process,and promote the training,guidance and management of different groups of students.
关键词
随机森林/成绩预测/R语言/数据挖掘Key words
Random forest/Grade prediction/R language/Data mining引用本文复制引用
基金项目
浙江省教育厅一般科研项目(Y202145896)
出版年
2024
NETL
NSTL
万方数据