科技创新与应用2025，Vol.15Issue(15)：24-27,4.DOI:10.19981/j.CN23-1581/G3.2025.15.005
BP-Adaboost算法在学业预警中的应用研究
俞骋1
作者信息
- 1. 宁波市教育科学研究所,浙江 宁波 315000
- 折叠
摘要
Abstract
Academic early warning technology based on machine learning is a research hotspot in the field of data mining.A review of relevant literature shows that although previous research has carried out a lot of explorations and proposed many algorithms for academic early warning based on machine learning,most of them have various flaws,which limit their large-scale popularization and application.To this end,this paper proposes an academic early warning algorithm based on BP-Adaboost model.A weak classifier is built through BP neural network,and a strong classifier is formed through Adaboost optimization.MATLAB simulation results show that the algorithm based on BP-Adaboost model can better filter out data with potential academic crises and achieve the purpose of early warning.关键词
BP-Adaboost/学业预警/数据挖掘/弱分类器/强分类器Key words
BP-Adaboost/academic early warning/data mining/weak classifier/strong classifier分类
计算机与自动化引用本文复制引用
俞骋..BP-Adaboost算法在学业预警中的应用研究[J].科技创新与应用,2025,15(15):24-27,4.
