Decision lists are a representation for Boolean functions which can be easily learnable from examples. Single term decision lists are more expressive than disjunctions and conjunctions; however, 1-term decision lists are less expressive than the general disjunctive normal form and the conjunctive normal form.
The language specified by a k-length decision list includes as a subset the language specified by a k-depth decision tree.
A decision list (DL) of length r is of the form:
if f1 then output b1 else if f2 then output b2 ... else if fr then output br
where fi is the ith formula and bi is the ith boolean for . The last if-then-else is the default case, which means formula fr is always equal to true. A k-DL is a decision list where all of formulas have at most k terms. Sometimes "decision list" is used to refer to a 1-DL, where all of the formulas are either a variable or its negation.
- Ronald L. Rivest (Nov 1987). "Learning decision lists" (PDF). Machine Learning. 2 (3): 229–246. doi:10.1023/A:1022607331053.
- Adam R. Klivans and Rocco A. Servedio, "Toward Attribute Efficient Learning of Decision Lists and Parities", Journal of Machine Learning Research 7:12:587-602 ACM Digital Library full text
|This artificial intelligence-related article is a stub. You can help Wikipedia by expanding it.|