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Table 1 Comparison of Random Forest and Support Vector Machine classifiers for predicting tissue-specific genes.

From: Genome-wide prediction and analysis of human tissue-selective genes using microarray expression data

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