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Table 11 Comparison of best classification accuracy for the Lung Cancer dataset

From: Accurate molecular classification of cancer using simple rules

Methods (feature selection + classification) #Selected genes #Correctly classified samples (accuracy) Rule-based classifier
depended degree + decision rules [this work] 1 145 (97.34%) yes
  2 144 (96.64%)  
attribute reduction + k-NNs [9] 2 146 (97.99%) no
PCLs [50] unknown 146 (97.99%) yes
C4.5 [50] 1 122 (81.88%) yes
Bagging [50] unknown 131 (87.92%) yes
Boosting [50] unknown 122 (81.88%) yes
SVMs [50] unknown 148 (99.33%) no
k-NNs [50] unknown 148 (99.33%) no
discretization + decision trees [11] unknown 139 (93.29%) yes
RCBT [13] 10-40 146 (97.99%) yes
gene expression ratios [15] 6 148 (99.33%) no