Decision Rule
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A Decision Rule is a rule whose consequent is a decision act.
- Context:
- It can be a Classification Rule.
- …
- Example(s):
- Counter-Example(s):
- See: Hierarchical Decision Rule, Decision Theory, Loss Function.
References
2012
- http://en.wikipedia.org/wiki/Decision_rule
- In decision theory, a decision rule is a function which maps an observation to an appropriate action. Decision rules play an important role in the theory of statistics and economics, and are closely related to the concept of a strategy in game theory.
In order to evaluate the usefulness of a decision rule, it is necessary to have a loss function detailing the outcome of each action under different states.
- In decision theory, a decision rule is a function which maps an observation to an appropriate action. Decision rules play an important role in the theory of statistics and economics, and are closely related to the concept of a strategy in game theory.
2011
- (Sammut & Webb, 2011) ⇒ Claude Sammut (editor), and Geoffrey I. Webb (editor). (2011). “Decision Rule.” In: (Sammut & Webb, 2011) p.262
- QUOTE: A decision rule is an element (piece) of knowledge, usually in the form of a “if-then statement”:
if < Condition > then < Action >
If its Condition is satisfied (i.e., matches a fact in the corresponding database of a given problem) then its Action (e.g., classification or decision making) is performed. See also Markovian Decision Rule.
- QUOTE: A decision rule is an element (piece) of knowledge, usually in the form of a “if-then statement”:
2007
- (Dembczyński et al., 2007) ⇒ Krzysztof Dembczyński, Salvatore Greco, Wojciech Kotłowski, and Roman Słowiński. (2007). “Statistical Model for Rough Set Approach to Multicriteria Classification.” In: Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases. ISBN:978-3-540-74975-2 doi:10.1007/978-3-540-74976-9_18
- QUOTE: … the equivalence of the variable consistency rough sets to the specific risk-minimizing decision rule in statistical ... 1 in the first problem form Cl1, while objects with new decision value ˆdi= 0... choosing the function f∗, which minimizes the empirical risk (29) with loss function (33) with...