Table 5.
Classification Results for SVM Models with 18 Additional Variable Combinations
| Noa. | Variable Set | Data Setb | Sensitivity (%) | Specificity (%) | Accuracy (%) |
|---|---|---|---|---|---|
| 7 | h-CLAT + Toolbox + 6 properties | Training | 97 | 97 | 97 |
| Test | 95 | 100 | 96 | ||
| 8 | KeratinoSens + Toolbox + Avg.Lys.Cys + 6 properties | Training | 99 | 100 | 99 |
| Test | 84 | 100 | 89 | ||
| 9 | KeratinoSens + h-CLAT + Avg.Lys.Cys + 6 properties | Training | 97 | 92 | 96 |
| Test | 90 | 86 | 89 | ||
| 10 | h-CLAT + Toolbox + Avg.Lys.Cys + 6 properties | Training | 96 | 96 | 96 |
| Test | 84 | 100 | 89 | ||
| 11 | KeratinoSens + h-CLAT + Toolbox + 6 properties | Training | 96 | 96 | 96 |
| Test | 90 | 86 | 89 | ||
| 12 | h-CLAT + KeratinoSens + 6 properties | Training | 94 | 89 | 93 |
| Test | 90 | 86 | 89 | ||
| 13 | h-CLAT + Avg.Lys.Cys + KeratinoSens + Toolbox + Log P | Training | 91 | 96 | 93 |
| Test | 90 | 86 | 89 | ||
| 14 | h-CLAT + Avg.Lys.Cys + 6 properties | Training | 96 | 92 | 95 |
| Test | 84 | 86 | 85 | ||
| 15 | Avg.Lys.Cys + Toolbox + 6 properties | Training | 91 | 100 | 94 |
| Test | 79 | 100 | 85 | ||
| 16 | h-CLAT + 6 properties | Training | 87 | 89 | 87 |
| Test | 90 | 86 | 89 | ||
| 17 | h-CLAT + Toolbox + Log P | Training | 81 | 92 | 84 |
| Test | 84 | 100 | 89 | ||
| 18 | Avg.Lys.Cys + KeratinoSens + 6 properties | Training | 93 | 96 | 94 |
| Test | 74 | 86 | 77 | ||
| 19 | Avg.Lys.Cys + KeratinoSens + Toolbox + Log P | Training | 88 | 92 | 89 |
| Test | 79 | 86 | 81 | ||
| 20 | Avg.Lys.Cys + 6 properties | Training | 85 | 100 | 89 |
| Test | 74 | 100 | 81 | ||
| 21 | Toolbox + 6 properties | Training | 90 | 81 | 87 |
| Test | 84 | 71 | 81 | ||
| 22 | KeratinoSens + Toolbox + 6 properties | Training | 91 | 85 | 89 |
| Test | 74 | 86 | 77 | ||
| 23 | KeratinoSens + 6 properties | Training | 79 | 89 | 82 |
| Test | 74 | 86 | 77 | ||
| 24 | 6 properties only | Training | 68 | 89 | 73 |
| Test | 73 | 71 | 73 |
Abbreviations: 6 properties = molecular weight, log octanol:water partition coefficient, log water solubility, log vapor pressure, melting point, and boiling point; Avg.Lys.Cys = average depletion for lysine and cysteine peptides from the direct peptide reactivity assay; h-CLAT = human cell line activation test; log P = log octanol:water partition coefficient; No. = number; SVM = support variable machine; Toolbox = read-across using QSAR Toolbox.
Models are listed in descending order of the average accuracy of the test and training sets.
The training set of 94 substances contains 68 LLNA sensitizers and 26 LLNA nonsensitizers. The test set of 26 substances contains 19 LLNA sensitizers and 7 LLNA nonsensitizers.