控制流量可以得到稳定的决策树

Proceedings 11th International Conference on Tools with Artificial Intelligence Pub Date : 1999-11-08 DOI:10.1109/TAI.1999.809802

Dimitris Kalles, Athanassios Papagelis

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引用次数: 0

摘要

本文研究了决策树增量归纳的稳定性问题。当归纳算法必须非常频繁地修改决策树，并且相似概念之间的振荡降低了学习速度时，稳定性问题就出现了。我们引入了一个启发式算法和一个有理论和实验支持的算法来解决这个问题。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Controlled flux results in stable decision trees

This work deals with stability in incremental induction of decision trees. Stability problems arise when an induction algorithm must revise a decision tree very often and oscillations between similar concepts decrease learning speed. We introduce a heuristic and an algorithm with theoretical and experimental backing to tackle this problem.

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Proceedings 11th International Conference on Tools with Artificial Intelligence

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