摘要
基于决策类划分的决策树算法用于较少的训练数据量推导有效已被验证,故选取较大数据集推演该算法并获取对应的多变量表达式。结果表明算法在较大数据量的数据集上同样有效,且表达式的规则覆盖范围并不小于数据量小的训练集。
The effectiveness of the decision tree algorithm based on decision class division had been verified on several smaller training datasets.A larger dataset was selected for the derivation of the algorithm and its corresponding multivariate expression was obtained.The result showed that the algorithm was equally effective on data sets with large data volume, and the rule coverage of the expression was not less than the training set with small amount of data.
作者
黄俊南
HUANG Junnan(Department of Information,Quanzhou Vocational College of Economics and Business,Quanzhou 362000,China)
出处
《新乡学院学报》
2019年第9期33-37,共5页
Journal of Xinxiang University
基金
福建省教育厅科技项目(JAT171059)
