Lossless fitness inheritance in genetic algorithms for decision trees

Details Lossless fitness inheritance in genetic algorithms for decision trees Lossless fitness inheritance in genetic algorithms for decision trees

2006-11-30

arxiv.org/abs/cs/0611166v2

Computer Science

Artificial Intelligence

Contains 23 pages, 6 figures, 12 tables. Text last updated as of March 6, 2009. Submitted to a journal

Scientific paper

When genetic algorithms are used to evolve decision trees, key tree quality parameters can be recursively computed and re-used across generations of partially similar decision trees. Simply storing instance indices at leaves is enough for fitness to be piecewise computed in a lossless fashion. We show the derivation of the (substantial) expected speed-up on two bounding case problems and trace the attractive property of lossless fitness inheritance to the divide-and-conquer nature of decision trees. The theoretical results are supported by experimental evidence.

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