Bagging One-Class Decision Trees

被引：6

作者：

Li, Chen ^{[1
]}

Zhang, Yang ^{[1
]}

机构：

[1] NW A&F Univ, Coll Informat Engn, Yangling 712100, Shaanxi Prov, Peoples R China

来源：

FIFTH INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY, VOL 2, PROCEEDINGS | 2008年

关键词：

D O I：

10.1109/FSKD.2008.478

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

POSC4.5 is a one-class decision tree classifier with good classification accuracy which learns from both positive and unlabeled examples. In order to further improve the classification accuracy and robustness of POSC4.5, in this paper, we ensemble POSC4.5 trees by bagging, and classify testing samples by majority voting. The experiment results on 5 UCI datasets show that the classification accuracy and robustness of POSC4.5 could be improved by our approach.

引用

页码：420 / 423

页数：4

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