基于随机森林的手写数字识别研究  

Research on Handwritten Digit Recognition Based on Random Forest

作　　者：陈晨[1] 颜雯嘉 CHEN Chen;YAN Wenjia(The First Affiliated Hospital of Xi'an Jiaotong University,Xi'an 710061,China;The Second Affiliated Hospital of Xi'an Jiaotong University,Xi'an 710004,China)

机构地区：[1]西安交通大学第一附属医院,陕西西安710061 [2]西安交通大学第二附属医院,陕西西安710004

出　　处：《佳木斯大学学报（自然科学版）》2024年第10期14-16,共3页Journal of Jiamusi University：Natural Science Edition

摘　　要：目前人工智能技术正在快速发展,应用在越来越多的领域,成为研究的热点,尤其是物体检测、图像识别方面。随机森林是贝叶斯网络的优化,是一种利用多个树分类器进行分类和预测的方法,可以降低分类识别过程中过拟合现象。基于随机森林的手写数字识别算法,探究随机森林算法在数字识别中的应用和优势,进行算法优化提高识别准确率。通过实验分析,结果表明提出的基于随机森林的手写数字识别算法具有较高的分类准确率和较好的泛化性能,能够满足实际应用需求。At present,artificial intelligence technology is rapidly developing and being applied in more and more fields,becoming a research hotspot,especially in object detection and image recognition.Random forest is an optimization of Bayesian networks that utilizes multiple tree classifiers for classification and prediction,which can reduce overfitting during the classification and recognition process.This article is based on the handwritten digit recognition algorithm of random forest,exploring the application and advantages of random forest algorithm in digit recognition,and optimizing the algorithm to improve recognition accuracy.Through experimental analysis,the results show that the handwritten digit recognition algorithm based on random forest proposed in this paper has high classification accuracy and good generalization performance,which can meet practical application needs.

关 键 词：手写数字 随机森林 决策树 节点 

分 类 号：TP393.1[自动化与计算机技术—计算机应用技术]