Table 3.
Performance evaluation metrics on the Aruba dataset without activities balancing using threefold cross-validation.
| Dataset | Cross-validation | Clustering method | Classification method | Precision (%) | Recall (%) | F score [0,1] | Accuracy (%) |
|---|---|---|---|---|---|---|---|
| Aruba | Threefolds | Fuzzy C-means [35] | ANN [45] | 84.50 | 84.70 | 0.84 | 84.70 |
| ET-KNN [47] | 80.60 | 80.80 | 0.80 | 80.80 | |||
| KNN [48] | 79.30 | 78.50 | 0.79 | 78.50 | |||
| SMO [46] | 75.37 | 74.02 | 0.74 | 74.02 | |||
| Hierarchical [42] | ANN | 82.80 | 83.80 | 0.82 | 83.80 | ||
| ET-KNN | 80.80 | 80.70 | 0.80 | 80.80 | |||
| KNN | 78.20 | 78.20 | 0.78 | 78.20 | |||
| SMO | 76.02 | 75.01 | 0.74 | 76.02 | |||
| K-mean [36] | ANN | 81.30 | 82.80 | 0.82 | 82.80 | ||
| ET-KNN | 79.50 | 79.80 | 0.79 | 79.80 | |||
| KNN | 77.50 | 78.20 | 0.78 | 78.20 | |||
| SMO | 74.20 | 75.01 | 0.74 | 75.02 | |||
| DBSCAN [37] | ANN | 79.20 | 80.80 | 0.80 | 80.80 | ||
| ET-KNN | 78.30 | 78.80 | 0.78 | 78.80 | |||
| KNN | 76.20 | 75.10 | 0.76 | 76.20 | |||
| SMO | 74.02 | 74.02 | 0.74 | 74.02 |
The precision, recall, and accuracy are in percentages (%), while the range of F score is between [0-1] with 1 being the highest. The highest values are in bold.