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 language | English |
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Title of host publication | Proceedings - 5th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2008 |
Publisher | IEEE, Institute of Electrical and Electronics Engineers |
Pages | 420-423 |
Number of pages | 4 |
Volume | 2 |
ISBN (Print) | 9780769533056 |
DOIs | |
Publication status | Published - 2008 |
Externally published | Yes |
Event | International Conference on Fuzzy Systems and Knowledge Discovery 2008 - Jinan, Shandong, China Duration: 18 Oct 2008 → 20 Oct 2008 Conference number: 5th |
Conference
Conference | International Conference on Fuzzy Systems and Knowledge Discovery 2008 |
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Abbreviated title | FSKD 2008 |
Country/Territory | China |
City | Jinan, Shandong |
Period | 18/10/08 → 20/10/08 |