Decision list
Decision lists are a representation for Boolean functions which can be easily learnable from examples.[1] 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.
Learning decision lists can be used for attribute efficient learning.[2]
Definition
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 [math]\displaystyle{ i \in \{1...r\} }[/math]. 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.
See also
References
- ↑ Ronald L. Rivest (Nov 1987). "Learning decision lists". Machine Learning 2 (3): 229–246. doi:10.1023/A:1022607331053. http://people.csail.mit.edu/rivest/pubs/Riv87b.pdf.
- ↑ 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
Original source: https://en.wikipedia.org/wiki/Decision list.
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