A general property among nested, pruned subtrees of a decision-support tree. (English) Zbl 0825.62125
Summary: Breiman, Friedman, Olshen, and Stone (1984) use a linear combination of prediction risk and tree size as a criterion in search of optimal trees. In this paper we use a linear combination of the above two components and the variable-observation cost as a criterion \((C_ 1)\) for the same purpose. This paper explicitly represents the relation among nested, pruned subtrees in terms of \(C_ 1\). Further, the theories in Breiman et al. (1984) concerning the search of optimal trees are generalized.
MSC:
| 62-XX | Statistics |
References:
| [1] | Arbab, B., Michie, D. and Joshi, A. Generating rules from examples. Proceedings of the Ninth International Joint Conference on Artificial Intelligence. Edited by: Joshi, A. Vol. 1, pp.631–633. Morgan Kaufmann Publishers. |
| [2] | DOI: 10.2307/2289296 · doi:10.2307/2289296 |
| [3] | Breiman L., Wadsworth International Group (1984) |
| [4] | DOI: 10.2307/2289295 · Zbl 0649.62055 · doi:10.2307/2289295 |
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| [6] | DOI: 10.2307/2283276 · Zbl 0114.10103 · doi:10.2307/2283276 |
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