Table 14 |
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|
Comparison of best classification accuracy for the Leukemia dataset 2 |
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|
Methods (feature selection + classification) |
#Selected genes |
#Correctly classified samples (accuracy) |
Rule-based classifier |
|
|
|||
|
α depended degree + decision rules [this work] |
1 |
14 (93.33%) |
yes |
|
|
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|
HykGene + k-NNs, SVMs, C4.5, NB [85] |
26 |
100%f |
noi |
|
|
|||
|
signal to noise ratios + k-NNs [20] |
40 |
95%g |
no |
|
|
|||
|
100 |
9 (90%)h |
||
|
|
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|
fLOOCV result in a total of 72 samples. gLOOCV result in a total of 57 training samples. hIn [20], only 3 of 8 AML testing samples in the dataset were mentioned. Thus, their test set contained 10 rather than 15 samples. iExcept for C4.5, all the others are not rule-based classifiers. |
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|
Wang and Gotoh BMC Medical Genomics 2009 2:64 doi:10.1186/1755-8794-2-64 |
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