From: Multi-sensor fusion based on multiple classifier systems for human activity identification
Positions | Methods | Accuracy (%) | Recall | Precision | F-measure | Errors | AUC |
---|---|---|---|---|---|---|---|
Ankle | SVM | 93.08 | 0.9029 | 0.9312 | 0.8987 | 0.0692 | 0.9465 |
KNN | 94.67 | 0.9243 | 0.9303 | 0.9272 | 0.0533 | 0.9272 | |
J48 | 95.13 | 0.9283 | 0.9380 | 0.9330 | 0.0487 | 0.9603 | |
LR | 95.60 | 0.9430 | 0.9382 | 0.9404 | 0.0440 | 0.9683 | |
Stacking–KNN–J48–KNN | 96.79 | 0.9592 | 0.9583 | 0.9587 | 0.0321 | 0.9772 | |
Stacking-LR–KNN–J48–LR | 97.49 | 0.9648 | 0.9673 | 0.9660 | 0.0251 | 0.9804 | |
Stacking–LR–KNN–J48–MV–LR–KNN | 97.57 | 0.9672 | 0.9669 | 0.9670 | 0.0243 | 0.9818 | |
Chest | SVM | 94.09 | 0.9107 | 0.9355 | 0.9210 | 0.0591 | 0.9505 |
KNN | 94.45 | 0.9148 | 0.9428 | 0.9275 | 0.0545 | 0.9528 | |
J48 | 93.35 | 0.9107 | 0.9185 | 0.9145 | 0.0665 | 0.9500 | |
LR | 95.32 | 0.9379 | 0.9373 | 0.9375 | 0.0468 | 0.9654 | |
Stacking-KNN–J48–KNN | 95.05 | 0.9323 | 0.9405 | 0.9362 | 0.0495 | 0.9621 | |
Stacking-LR–KNN–J48–LR | 95.67 | 0.9398 | 0.9477 | 0.9435 | 0.0433 | 0.9665 | |
Stacking-LR–KNN–J48–MV–LR–KNN | 96.02 | 0.9425 | 0.9528 | 0.9474 | 0.0398 | 0.9681 | |
Wrist | SVM | 90.96 | 0.8432 | 0.9293 | 0.8758 | 0.0904 | 0.9134 |
KNN | 93.32 | 0.8828 | 0.9514 | 0.9111 | 0.0668 | 0.9311 | |
J48 | 91.89 | 0.8885 | 0.9020 | 0.8947 | 0.0811 | 0.9376 | |
LR | 91.38 | 0.8780 | 0.8884 | 0.8828 | 0.0862 | 0.9323 | |
Stacking-KNN–J48–KNN | 94.74 | 0.9209 | 0.9448 | 0.9319 | 0.0526 | 0.9560 | |
Stacking-LR–KNN–J48–LR | 95.32 | 0.9324 | 0.9472 | 0.9395 | 0.0468 | 0.9623 | |
Stacking-LR–KNN–J48–MV–LR–KNN | 95.48 | 0.9330 | 0.9501 | 0.9412 | 0.0452 | 0.9628 |