New heuristic algorithm optimizes data analysis for improved decision-making efficiency.
Researchers developed heuristic algorithms to reduce attributes in variable precision rough sets. They analyzed attribute significance using different measures like attribute dependence and mutual information. The algorithms aim to find the least reduction while maintaining accuracy and coverage. The algorithms were tested using MATLAB and proved to be effective in a practical example.