计算机工程与应用2012，Vol.48Issue(33)：194-196,211,4.DOI:10.3778/j.issn.1002-8331.1207-0203
基于Bagging集成学习的字符识别方法
Research on character recognition based on Bagging ensemble learning
摘要
Abstract
Due to the diversity of character recognition, a character recognition model based on Bagging ensemble is presented, which solves recognition model' s preferences for certain character. Different datasets are formed by Bagging, and then base-classifier is constructed. Ensemble learning model is built by majority vote. Theoretic analysis and simulation result shows the model owns better classification accuracy than other classification methods.关键词
Bagging/字符识别/集成学习/决策树/AdaboostKey words
Bagging/ character recognition/ ensemble learning/ decision tree/ Adaboost分类
信息技术与安全科学引用本文复制引用
刘余霞,吕虹,胡涛,孙小虎..基于Bagging集成学习的字符识别方法[J].计算机工程与应用,2012,48(33):194-196,211,4.基金项目
国家自然科学基金(No.61071001) （No.61071001）
安徽省教育厅自然科学基金(No.KJ2008A010). （No.KJ2008A010）
