基于合群度-隶属度噪声检测及动态特征选择的改进AdaBoost算法
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王友卫,凤丽洲
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Improved AdaBoost algorithm using group degree and membership degree based noise detection and dynamic feature selection
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You-wei WANG,Li-zhou FENG
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| 表 6 不同特征选择方法的平均运行时间增幅均值比较 |
| Tab.6 Comparison of average increments of average running time values of different feature selection methods |
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| 数据集 | rai | | IGW vs IG | CHIW vs CHI | MRMRW vs MRMR | CMFSW vs CMFS | | Spambase | 0.007 | 0.011 | 0.013 | 0.016 | | AD | 0.126 | 0.131 | 26.927 | 0.107 | | KDD99 | 0.013 | 0.016 | 0.005 | 0.018 | | DrivFace | 0.806 | 1.275 | 4.572 | 0.586 | | Arrhythmia | 0.172 | 0.265 | 0.004 | 0.052 | | AntiVirus | 0.005 | 0.008 | 0.006 | 0.001 | | Dermatology | 0.000 | 0.001 | 0.000 | 0.000 | | Amazon | 0.412 | 0.307 | 53.862 | 0.465 | | All datasets | 0.192 | 0.251 | 10.673 | 0.155 |
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