加权变精度直觉模糊序信息决策表的近似约简
|
|
徐伟华, 潘彦舟
|
Approximate reduction in weighted variable precision intuitionistic fuzzy ordered decision table
|
|
Weihua Xu, Yanzhou Pan
|
|
表7 不同算法在BayesNet和RandomTree上的分类精度
|
Table 7 Comparative classification results of three algorithms on BayesNet and RandomTree
|
|
| 数据集 | BayesNet | RandomTree |
|---|
| VDR | VUR | MR | VDR | VUR | MR |
|---|
| Average | 83.72%±6.14% | 83.68%±6.69% | 81.76%±7.79% | 89.83%±7.18% | 89.82%±8.26% | 84.85%±5.89% | | Wine | 95.00%±4.99% | 93.00%±7.37% | 90.98%±2.18% | 98.00%±8.19% | 98.33%±7.37% | 92.67%±1.74% | | Seeds | 95.48%±6.94% | 96.9%±7.9% | 97.14%±5.71% | 96.67%±7.64% | 95.00%±8.12% | 93.81%±7.62% | | Heart | 83.33%±12.62% | 82.22%±10.48% | 87.78%±20.76% | 89.96%±3.18% | 88.89%±7.45% | 82.22%±11.60% | | Forest | 97.14%±5.71% | 97.14%±5.71% | 94.46%±6.55% | 98.75%±9.01% | 98.57%±9.46% | 95.71%±6.8% | | Wdbc | 95.88%±3.90% | 95.39%±4.88% | 90.03%±5.44% | 96.47%±5.29% | 97.06%±6.34% | 91.80%±4.88% | | Aust | 82.67%±7.03% | 82.67%±7.05% | 72.55%±10.18% | 88.40%±6.69% | 87.43%±5.98% | 75.41%±5.73% | | German | 67.47%±4.16% | 69.33%±5.78% | 68.00%±8.14% | 73.33%±12.83% | 76.33%±14.59% | 70.33%±5.59% | | Health | 61.69%±6.28% | 62.01%±7.51% | 62.01%±6.96% | 74.39%±6.67% | 74.73%±9.30% | 76.42%±9.30% | | Card | 74.59%±3.63% | 74.44%±3.48% | 72.89%±4.18% | 92.47%±5.12% | 91.20%±5.74% | 84.59%±4.73% |
|
|
|