Table 6 The results of different classifiers and testing samples using XGBoost
From: A universal Wi-Fi fingerprint localization method based on machine learning and sample differences
Model-test | GBDT | XGBoost | ||||
|---|---|---|---|---|---|---|
Floor success rate (%) | Point success rate (%) | Mean error (m) | Floor success rate (%) | Point success rate (%) | Mean error (m) | |
M0-T0 | 100.00 | 78.52 | 1.399 | 99.22 | 66.41 | 2.414 |
M0-T1 | 100.00 | 81.63 | 2.927 | 100.00 | 70.41 | 4.336 |
M0-T2 | 96.39 | 54.12 | 6.005 | 100.00 | 60.31 | 4.808 |
M1-T0 | 99.22 | 59.38 | 3.002 | 96.48 | 46.09 | 4.639 |
M1-T1 | 98.98 | 76.53 | 2.873 | 98.98 | 65.31 | 4.269 |
M1-T2 | 93.81 | 52.06 | 7.257 | 99.49 | 55.16 | 5.109 |
M2-T0 | 100.00 | 75.00 | 1.803 | 98.83 | 55.86 | 3.122 |
M2-T1 | 100.00 | 78.06 | 2.804 | 100.00 | 67.86 | 3.936 |
M2-T2 | 98.45 | 74.49 | 3.089 | 100.00 | 62.11 | 3.563 |
Mean | 98.54 | 69.98 | 3.460 | 99.22 | 61.06 | 4.022 |