The positive, negative, and boundary regions can be interpreted as regions of acceptance, rejection, and deferment decisions, respectively.
The probabilistic rough set model extends the conventional rough sets by providing a more effective way of classifying objects.
A main result of probabilistic rough sets is the interpretation of three-way decisions using a pair of probabilistic thresholds.
The game-theoretic rough set model determines and interprets the required thresholds by utilizing a game-theoretic environment for analyzing strategic situations between cooperative or conflicting decision-making criteria.
The essential idea is to implement a game for investigating how the probabilistic thresholds may change in order to improve the rough set-based decision-making.