The aim of this article is to present a new approach to machine learning (precisely in classification problems) in which the use of fuzzy logic has been taken into account. We intend to show that fiazzy logic introduces new elements in the identification process, mainly due to the facility to manage
Acquisition of uncertain rules in a probabilistic logic
β Scribed by John G. Cleary
- Publisher
- Elsevier Science
- Year
- 1987
- Weight
- 509 KB
- Volume
- 27
- Category
- Article
- ISSN
- 0020-7373
No coin nor oath required. For personal study only.
β¦ Synopsis
The problem of acquiring uncertain rules from examples is considered. The uncertain rules are expressed using a simple probabilistic logic which obeys all the axioms of propositional logic. By using three truth values (true, false, undefined) a consistent expression of contradictory evidence is obtained. As well the logic is able to express the correlations between rules and to deal with uncertain rules where the probabilities of correlations between the rules can be directly computed from examples.
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