Table 1

Comparison of Random Forest and Support Vector Machine classifiers for predicting tissue-specific genes.

Tissue

Method

AC

(%)

SN

(%)

SP

(%)

MCC

ROC

AUC


Brain

SVM

92.07

(± 0.302)

54.23

(± 1.227)

95.82 (± 0.263)

0.5091 (± 0.015)

0.8937

(± 0.003)


RF

93.48

(± 0.240)

53.73

(± 1.485)

97.43 (± 0.153)

0.5676 (± 0.016)

0.9488 (± 0.002)


Liver

SVM

97.29

(± 0.421)

84.11

(± 2.281)

98.61 (± 0.309)

0.8350 (± 0.025)

0.9854 (± 0.004)


RF

97.29

(± 0.341)

79.00

(± 1.355)

99.12 (± 0.255)

0.8290 (± 0.0213)

0.9777 (± 0.002)


The values outside and inside brackets are the average value and standard deviation of measures in ten classifier evaluations, respectively.

Teng et al. BMC Medical Genomics 2013 6(Suppl 1):S10   doi:10.1186/1755-8794-6-S1-S10

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