Breast Cancer Classification from Mammogram Images Using Extreme Learning Machine-Based DenseNet121 Model

Table 5

Performance measure results of the models with batch size 64.

Models	No. of iteration	Specificity	Sensitivity	Training accuracy	Testing accuracy	Computational time in minutes
VGG19	100	97.81	98.05	94.63	91.64	214.3589
MobileNet	100	98.61	98.47	94.97	92.75	202.2457
Xception	100	98.93	98.87	95.65	94.24	198.3321
ResNet50V2	100	98.64	98.44	95.95	94.67	197.3123
InceptionV3	100	100	99.57	96.29	95.64	187.3125
InceptionResNetV2	100	98.67	100	96.69	96.51	171.2487
DenseNet201	100	98.67	99.35	97.29	97.5	168.4589
DenseNet121	100	99.35	100	98.41	97.97	164.5278
DenseNet121+ELM	100	99.45	100	99.34	98.53	163.8975