Research Article
Diagnosing the Stage of Hepatitis C Using Machine Learning
Table 4
Confusion matrix for the proposed IHSDS during training.
| Proposed IHSDS model (70% of the dataset in training) | N = 968 (no. of samples) | Predicted output (Ƥ0, Ƥ1, Ƥ2, Ƥ3) | Actual output (ƴ0, ƴ1, ƴ2, ƴ3) | Ƥ0 (Stage I) | Ƥ1 (Stage II) | Ƥ2 (Stage III) | Ƥ3 (Stage IV) |
| Input | | | | | ƴ0 = 235 (Stage I) | 159 | 28 | 15 | 16 | ƴ1 = 232 (Stage II) | 29 | 182 | 17 | 21 | ƴ2 = 248 (Stage III) | 19 | 13 | 200 | 16 | ƴ3 = 253 (Stage IV) | 17 | 18 | 25 | 193 |
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