Research Article
Deep Neural Network for Somatic Mutation Classification
Table 2
The performances of somatic mutation detection by SVM, RF, and forgeNet.
| ā | SN | SP | Acc | MCC | F1 |
| Dataset 1 | forgeNet | 0.986 | 0.954 | 0.972 | 0.943 | 0.976 | SVM | 0.977 | 0.956 | 0.968 | 0.935 | 0.972 | RF | 0.983 | 0.964 | 0.975 | 0.949 | 0.978 |
| Dataset 2 | forgeNet | 0.933 | 0.989 | 0.981 | 0.917 | 0.928 | SVM | 0.933 | 0.967 | 0.963 | 0.847 | 0.865 | RF | 0.870 | 0.997 | 0.981 | 0.915 | 0.923 |
| Dataset 3 | forgeNet | 0.971 | 0.986 | 0.982 | 0.957 | 0.97 | SVM | 0.974 | 0.978 | 0.977 | 0.946 | 0.962 | RF | 0.961 | 0.991 | 0.982 | 0.956 | 0.969 |
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