Name
Abstract | ||
|---|---|---|
In dealing with risk in real decision problems, decision-theoretic rough sets with loss functions aim to obtain optimization decisions by minimizing the overall risk with Bayesian decision procedures. Two parameters generated by loss functions divide the universe into three regions as the decision of acceptance, deferment and rejection. In this paper, we discuss the semantics of loss functions, and utilize the differences of losses replace actual losses to construct a new ''four-level'' approach of probabilistic rules choosing criteria. Ten types of probabilistic rough set models can be generated by the ''four-level'' approach and form two groups of models: two-way probabilistic decision models and three-way probabilistic decision models. A reasonable decision with these criteria is demonstrated by an illustration of oil investment. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1016/j.ins.2011.04.039 | Inf. Sci. |
Keywords | Field | DocType |
three-way probabilistic decision model,real decision problem,loss function,actual loss,optimization decision,probabilistic rule,probabilistic rough set model,two-way probabilistic decision model,reasonable decision,probabilistic model criterion,decision-theoretic rough set,bayesian decision procedure,rough set,decision models,decision problem,probabilistic model | Decision rule,Decision analysis,Decision tree,Optimal decision,Influence diagram,Weighted sum model,Artificial intelligence,Evidential reasoning approach,Machine learning,Dominance-based rough set approach,Mathematics | Journal |
Volume | Issue | ISSN |
181 | 17 | 0020-0255 |
Citations | PageRank | References |
96 | 1.96 | 37 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dun Liu | 1 | 1526 | 46.87 |
| Tianrui Li | 2 | 3176 | 191.76 |
| Da Ruan | 3 | 2008 | 112.05 |