Cost-Sensitive Attribute Reduction in Decision-Theoretic Rough Set Models
Figure 1
Assuming that ALF is around 500 and 3000, respectively, the effectiveness of the heuristic algorithm is measured by using two metrics. (a) Finding optimal factor (FOF) is the fraction of successful searches of an optimal reduct in experiments. The higher the FOF is, the better the heuristic algorithm is. It is shown that all FOF are above 0.5. (b) Average exceeding factor (AEF) is the average value of the fractions beyond the minimal-average-total costs. The lower the AEF, the better the algorithm. All AEF are below 0.1 in the figure.
