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) |