关键词: Bagging, 字符识别, 集成学习, 决策树, Adaboost

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.

Key words: Bagging, character recognition, ensemble learning, decision tree, Adaboost