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