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

Table 4

Performance measure results of the models with batch size 32.

Models	No. of iteration	Specificity	Sensitivity	Training accuracy	Testing accuracy	Computational time in minutes
VGG19	100	97.73	97.98	94.74	90.44	219.8159
MobileNet	100	98.53	98.4	95.08	91.55	210.7027
Xception	100	98.85	98.8	95.76	93.04	199.8891
ResNet50V2	100	98.56	98.37	96.06	93.47	198.8683
InceptionV3	100	100	99.52	96.4	94.44	194.7695
InceptionResNetV2	100	98.59	100	96.8	95.31	178.7057
DenseNet201	100	98.59	99.28	97.4	96.3	174.9159
DenseNet121	100	99.27	100	97.52	96.77	171.9848
DenseNet121+ELM	100	99.37	99.94	98.67	97.33	167.3545