Bagging one-class decision trees

Chen Li, Yang Zhang

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

6 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationProceedings - 5th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2008
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages420-423
Number of pages4
Volume2
ISBN (Print)9780769533056
DOIs
Publication statusPublished - 2008
Externally publishedYes
EventInternational Conference on Fuzzy Systems and Knowledge Discovery 2008 - Jinan, Shandong, China
Duration: 18 Oct 200820 Oct 2008
Conference number: 5th

Conference

ConferenceInternational Conference on Fuzzy Systems and Knowledge Discovery 2008
Abbreviated titleFSKD 2008
CountryChina
CityJinan, Shandong
Period18/10/0820/10/08

Cite this