Table 14

Comparison of best classification accuracy for the Leukemia dataset 2

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


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


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.

Wang and Gotoh BMC Medical Genomics 2009 2:64   doi:10.1186/1755-8794-2-64

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