摘要
介绍了Naive Bayes算法的基本理论。以UCI数据库中的大豆数据集为实例,研究了Naive Bayes算法在大豆病害诊断中的应用。试验结果表明,Naive Bayes算法的预测精度优于决策树C4.5算法和最近邻INN算法。
The basic theory of Naive Bayes algorithm was firstly introduced.Taking the soybean dataset in UCI database as an example,the applications of Naive Bayes algorithm in soybean disease diagnosis were studied.The research results indicated the prediction accuracy of Naive Bayes algorithm was better than that of decision tree C4.5 algorithm and nearest neighbor INN algorithm.
出处
《安徽农业科学》
CAS
北大核心
2009年第11期5320-5320,5323,共2页
Journal of Anhui Agricultural Sciences