Table 3 Models comparison. T-test p-value from bootstrap results on the testing sets
From: A machine learning approach for predicting methionine oxidation sites
Feature set | RF-SVM | RF-NN | SVM-NN |
|---|---|---|---|
AUC | |||
Primary | 1.337807e-53 | 1.656090e-52 | 3.629288e-01 |
Tertiary | 7.466593e-08 | 7.749183e-10 | 3.076722e-01 |
Whole | 1.620777e-11 | 1.207725e-10 | 6.687422e-01 |
mRMR | 5.736385e-04 | 1.122952e-05 | 3.027066e-01 |
Accuracy | |||
Primary | 7.466593e-08 | 7.749183e-10 | 3.076722e-01 |
Tertiary | 1.620777e-11 | 1.207725e-10 | 6.687422e-01 |
Whole | 5.736385e-04 | 1.122952e-05 | 3.027066e-01 |
mRMR | 1.110837e-35 | 7.810002e-38 | 5.302538e-01 |
Sensitivity | |||
Primary | 4.838807e-26 | 9.923600e-27 | 8.419212e-01 |
Tertiary | 7.067182e-08 | 2.630463e-04 | 3.507737e-02 |
Whole | 3.771161e-17 | 6.241079e-09 | 1.096249e-02 |
mRMR | 1.650447e-03 | 5.410619e-02 | 1.924156e-01 |
Specificity | |||
Primary | 7.035627e-39 | 8.036713e-20 | 3.721847e-07 |
Tertiary | 1.059365e-30 | 6.066923e-15 | 1.807435e-05 |
Whole | 1.072350e-21 | 9.069624e-16 | 3.319756e-02 |
mRMR | 7.569818e-06 | 2.475176e-09 | 1.699726e-01 |
F-measure | |||
Primary | 1.900064e-14 | 8.911586e-10 | 4.341598e-02 |
Tertiary | 1.385330e-43 | 3.632520e-39 | 5.440616e-01 |
Whole | 8.253875e-35 | 1.802488e-31 | 3.612268e-01 |
mRMR | 5.984561e-23 | 4.366711e-19 | 3.520361e-02 |
MCC | |||
Primary | 9.137039e-07 | 8.985178e-06 | 5.212807e-01 |
Tertiary | 1.701737e-16 | 1.821765e-13 | 8.146449e-02 |
Whole | 6.201029e-44 | 2.659090e-33 | 2.914253e-03 |
mRMR | 4.996287e-36 | 3.033082e-28 | 7.392408e-03 |