基于朴素Bayes组合的简易集成分类器  

Simply Constructed Ensemble Classifier Based on Naive Bayes Combination

作　　者：宋丛威 SONG Cong-Wei(School of Science,Zhijiang College of Zhejiang University of Technology,Shaoxing 312030,China)

机构地区：[1]浙江工业大学之江学院理学院,绍兴312030

出　　处：《计算机系统应用》2021年第2期265-267,共3页Computer Systems & Applications

基　　金：浙江省自然科学基金(LQ19F050004)。

摘　　要：朴素Bayes分类器是一种简单有效的机器学习工具.本文用朴素Bayes分类器的原理推导出“朴素Bayes组合”公式,并构造相应的分类器.经过测试,该分类器有较好的分类性能和实用性,克服了朴素Bayes分类器精确度差的缺点,并且比其他分类器更加快速而不会显著丧失精确度.Naive Bayes classifier is a simple and effective machine learning tool.Based on the principle of naive Bayes classifier,this study deduces the formula of“naive Bayes combination”and constructs the corresponding classifier.It is found through testing that the classifier has superior classification performance and practicality as it overcomes the shortcoming of poor accuracy of naive Bayes classifier and is faster than other classifiers without significant loss of accuracy.

关 键 词：朴素Bayes分类器 朴素Bayes组合 集成学习 条件独立性 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]