dominancebased
Dominancebased refers to a family of methods in decision analysis, machine learning, and optimization that rely on dominance relations among alternatives across multiple criteria. The central idea is that one option can be considered preferable to another if it is at least as good in all criteria and better in at least one, i.e., it Pareto-dominates the other. In practice, dominance-based approaches use these relations to classify, rank, or select options, often handling trade-offs between conflicting objectives or attributes with different scales and directions.
A notable instantiation is the dominance-based rough set approach (DRSA), which extends rough set theory to
Dominance-based methods are widely used in multi-criteria decision analysis, optimization, and data mining. They support tasks