Table 13 Statistics by the class of different classifiers with human activity recognition using smartphones dataset (6 features)
From: Selecting critical features for data classification based on machine learning methods
Evaluation | Class: LAYING | Class: SITTING | Class: STANDING | Class: WALKING | Class: WALKING_DOWNSTAIRS | Class: WALKING_UPSTAIRS |
|---|---|---|---|---|---|---|
RF + SVM Accuracy: 0.8685 | ||||||
 Precision | 1.0000 | 0.8604 | 0.8910 | 0.7527 | 0.8966 | 0.8030 |
 Recall | 1.0000 | 0.8872 | 0.8650 | 0.8571 | 0.7919 | 0.7617 |
RF + LDA Accuracy: 0.8297 | ||||||
 Precision | 0.9860 | 0.8791 | 0.7949 | 0.7128 | 0.8182 | 0.78107 |
 Recall | 1.0000 | 0.7354 | 0.9051 | 0.8408 | 0.8223 | 0.61682 |
RF + KNN Accuracy: 0.904 | ||||||
 Precision | 1.0000 | 0.9125 | 0.9366 | 0.8083 | 0.8783 | 0.8657 |
 Recall | 1.0000 | 0.9339 | 0.9161 | 0.8776 | 0.8426 | 0.8131 |
RF + RF Accuracy: 0.9326 | ||||||
 Precision | 1.0000 | 0.9240 | 0.9478 | 0.8984 | 0.9031 | 0.9019 |
 Recall | 1.0000 | 0.9455 | 0.9270 | 0.9020 | 0.8985 | 0.9019 |