Validated decision trees versus collective decisions

Authors:
Krzysztof Grąbczewski
Affiliations:
Department of Informatics, Nicolaus Copernicus University, Toruń, Poland
Venue:
ICCCI'11 Proceedings of the Third international conference on Computational collective intelligence: technologies and applications - Volume Part II
Year:
2011

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Abstract

In the most common decision tree (DT) induction approaches, crossvalidation based processes validate the final DT model. This article answers many questions about advantages of using different types of committees constructed from the DTs generated within the validation process, over single validated DTs. Some new techniques of providing committee members and their collective decisions are introduced and evaluated among other methods. The conclusions presented here, are useful both for human experts and automated meta-learning approaches.