1991 RuleInductionUsingInformationTheory

• (Smyth & Goodman, 1991) ⇒ Padhraic Smyth, Rodney M. Goodman. (1991). “Rule Induction Using Information Theory.” In: Proceedings on the Workshop on Knowledge Discovery in Databases (KDD 1991)

Subject Headings: Probabilistic Rule.

Cited By

~263 http://scholar.google.com/scholar?cites=3541875441104994878

Quotes

9.2 The Probabilistic Rule Representation

• We define a probabilistic rule as an if-then statement to the effect that if proposition [math]\displaystyle{ y }[/math] occurs then there is a probability [math]\displaystyle{ p }[/math] that proposition [math]\displaystyle{ x }[/math] is true and a probability 1 - [math]\displaystyle{ p }[/math] that proposition not x is true. It is convenient to define the probability [math]\displaystyle{ p }[/math] as the conditional probability p(x|y). Hence our probabilistic rule corresponds to a simple statement regarding the conditional probability of one event given another. While other methods of representing uncertainty have been proposed and are in common use (such as fuzzy logic (Zaheh 1965) and certainty factors (Adams 1976)), standard probability theory remains the established and preferred uncertainty model due to its theoretical foundations and proven utility.

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
1991 RuleInductionUsingInformationTheory	Padhraic Smyth Rodney M. Goodman			Rule Induction Using Information Theory		Proceedings on the Workshop on Knowledge Discovery in Databases	http://www.rodgoodman.ws/pdf/RG.Paper.BC7.pdf			1991