Uncertainty in Artificial Intelligence
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Decision Tree Induction Systems: A Bayesian Analysis
Wray Buntine
Abstract:
Decision tree induction systems are being used for knowledge acquisition in noisy domains. This paper develops a subjective Bayesian interpretation of the task tackled by these systems and the heuristic methods they use. It is argued that decision tree systems implicitly incorporate a prior belief that the simpler (in terms of decision tree complexity) of two hypotheses be preferred, all else being equal, and that they perform a greedy search of the space of decision rules to find one in which there is strong posterior belief. A number of improvements to these systems are then suggested.
Keywords: Decision Trees, Bayesian Interpretation
Pages: 109-127
PS Link:
PDF Link: /papers/87/p109-buntine.pdf
BibTex:
@INPROCEEDINGS{Buntine87,
AUTHOR = "Wray Buntine ",
TITLE = "Decision Tree Induction Systems: A Bayesian Analysis",
BOOKTITLE = "Uncertainty in Artificial Intelligence 3 Annual Conference on Uncertainty in Artificial Intelligence (UAI-87)",
PUBLISHER = "Elsevier Science",
ADDRESS = "Amsterdam, NL",
YEAR = "1987",
PAGES = "109--127"
}


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