Table 3 Multi-class classification report for logistics regression (LR), decision trees (DT) and support vector machines (SVM) tested on the experimental battery compounds data set, encoded using Mendeleev encoding
From: Classification of battery compounds using structure-free Mendeleev encodings
Classification | Algorithm | Metric | Class 0 | Class 1 | Class 2 | Class 3 | Class 4 |
|---|---|---|---|---|---|---|---|
|  |  | Precision | 1.000 | 1.000 | — | — | — |
|  | LR | Recall | 1.000 | 0.997 | — | — | — |
|  |  | Accuracy | 1.00 | 0.998 | — | — | — |
|  |  | Precision | 1.000 | 1.000 | — | — | — |
Binary | DT | Recall | 1.000 | 1.000 | — | — | — |
|  |  | Accuracy | 1.000 | 1.000 | — | — | — |
|  |  | Precision | 1.000 | 1.000 | — | — | — |
|  | SVM | Recall | 1.000 | 0.998 | — | — | — |
|  |  | Accuracy | 1.000 | 0.999 | — | — | — |
| Â | Â | Precision | 0.996 | 0.996 | 0.992 | 1.000 | 0.999 |
| Â | LR | Recall | 0.998 | 0.992 | 0.992 | 1.000 | 0.996 |
| Â | Â | Accuracy | 0.997 | 0.994 | 0.992 | 1.000 | 0.997 |
| Â | Â | Precision | 1.000 | 0.999 | 0.996 | 0.995 | 1.000 |
Multi-class | DT | Recall | 1.000 | 1.000 | 1.000 | 1.000 | 0.999 |
| Â | Â | Accuracy | 1.000 | 1.000 | 0.998 | 0.997 | 1.000 |
| Â | Â | Precision | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 |
| Â | SVM | Recall | 1.000 | 1.000 | 0.988 | 0.989 | 0.995 |
| Â | Â | Accuracy | 1.000 | 1.000 | 0.994 | 0.999 | 0.997 |