Table 1 Performance of classification algorithms for the leukemia data based on 20 repetitions of 10-fold CV
From: Classification methods for the development of genomic signatures from high-dimensional data
Algorithm | Accuracy | Sensitivity* | Specificity†| PPV‡ | NPV§ |
|---|---|---|---|---|---|
CERP | 98.6 (<.001) | 96.0 (<.001) | 100.0 (.000) | 100.0 (.000) | 97.9 (<.001) |
RF | 97.9 (.008) | 95.0 (.022) | 99.5 (.009) | 99.0 (.018) | 97.4 (.011) |
AdaBoost | 96.0 (.005) | 95.6 (.012) | 96.3 (.009) | 93.2 (.016) | 97.6 (.006) |
SVM | 97.2 (.012) | 92.0 (.034) | 100.0 (.000) | 100.0 (.000) | 95.9 (.017) |
DLDA | 97.5 (.007) | 96.0 (<.001) | 98.3 (.011) | 96.8 (.021) | 97.9 (<.001) |
SC | 96.0 (.004) | 96.0 (<.001) | 96.0 (.007) | 92.7 (.011) | 97.8 (<.001) |
CART | 81.7 (.035) | 76.2 (.046) | 84.6 (.053) | 72.4 (.067) | 87.0 (.021) |
CRUISE | 86.8 (.021) | 79.8 (.040) | 90.5 (.029) | 82.0 (.044) | 89.4 (.018) |
QUEST | 86.9 (.020) | 79.4 (.042) | 91.0 (.032) | 82.7 (.048) | 89.3 (.018) |