Skip to main content

Table 4 Comparative experimental results of the best subsets produced by mABC and other methods for different datasets

From: Gene selection for cancer classification with the help of bees

Dataset name Evaluation EPSO   IBPSO   TS-BPSO   BPSO-CGA   Random forest   mABC
  Criteria [37]   [43]   [42]   [44]   [55]   [This work]
   Best Avg. S.D.   Best   Best   Best   Avg. S.D.   Best Avg. S.D.
9_Tumors Accuracy 76.67 75.00 1.11   78.33   81.63   -   88.0 0.037   100 98.65 0.01
  # Genes 251 247.10 9.65   1280   2941   -   130 -   30 34.73 5.64
11_Tumors Accuracy 96.55 95.40 0.61   93.10   97.35   -   - -   100 99.50 0.00
  # Genes 243 237.70 9.66   2948   3206   -   - -   42 47.27 7.79
Brain_Tumor1 Accuracy 93.33 92.11 0.82   94.44   95.89   91.4   93.6 0.007   100 100 0.0
  # Genes 8 7.5 2.51   754   2913   456   86 -   12 16.87 2.85
Brain_Tumor2 Accuracy 94 92.4 1.27   94.00   92.65   -   - -   100 100 0.0
  # Genes 4 6.0 1.83   1197   5086   -   - -   7 10.52 1.72
DLBCL Accuracy 100 100 0   100   100   -   94.6 0.021   100 100 0.0
  # Genes 3 4.7 0.82   1042   2671   -   21 -   3 4.05 0.78
Leukemia1 Accuracy 100 100 0   100   100   100   98.1 0.006   100 100 0.0
  # Genes 2 3.20 0.63   1034   2577   300   21 -   4 5.67 0.73
Leukemia2 Accuracy 100 100 0   100   100   -   - -   100 100 0.0
  # Genes 4 6.8 2.2   1292   5609   -   - -   4 6.29 0.98
Lung_Cancer Accuracy 96.06 95.67 0.31   96.55   99.52   -   - -   100 100 0.0
  # Genes 7 8.3 2.11   1897   6958   -   - -   14 23.31 5.14
Prostate_Tumor Accuracy 99.02 97.84 0.62   92.16   95.45   93.7   - -   100 100 0.0
  # Genes 5 6.6 2.17   1294   5320   795   - -   5 10.73 3.15
SRBCT Accuracy 100 99.64 0.58   100   100   100   99.7 0.003   100 100 0.0
  # Genes 7 14.90 13.03   431   1084   880   42 -   5 5.59 0.51
  1. Best results (maximum accuracy and minimum selected gene size) are highlighted using boldface font