Abstract
In the most common decision tree (DT) induction approaches, cross-validation 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.
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Grąbczewski, K. (2011). Validated Decision Trees versus Collective Decisions. In: Jędrzejowicz, P., Nguyen, N.T., Hoang, K. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2011. Lecture Notes in Computer Science(), vol 6923. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23938-0_35
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DOI: https://doi.org/10.1007/978-3-642-23938-0_35
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