Multiclass Cancer Prediction Based on Copy Number Variation Using Deep Learning

Table 3

The classwise performances of all networks.

Models	GBM (3)	KIRC(4)	HNSC(5)	COAD/READ(2)	BLCA(1)	BRCA(0)
NN
TP rate	0.68	0.96	0.82	0.98	0.83	0.93
ROC area	0.97	0.99	0.97	1.00	0.98	0.99
Precision	0.77	0.90	0.92	0.93	0.81	0.97
F-measure	0.72	0.93	0.87	0.96	0.82	0.95
Recall	0.68	0.96	0.82	0.98	0.83	0.93
FP rate	0.00	0.01	0.04	0.01	0.02	0.00
DNN
TP rate	0.72	0.96	0.85	0.98	0.85	0.94
ROC area	0.97	0.98	0.99	1.00	0.98	0.99
Precision	0.75	0.93	0.94	0.94	0.85	0.93
F-measure	0.73	0.94	0.89	0.96	0.85	0.94
Recall	0.72	0.96	0.85	0.98	0.85	0.94
FP rate	0.01	0.02	0.01	0.01	0.01	0.01
LSTM
TP rate	0.52	0.95	0.85	0.98	0.88	0.92
ROC area	0.96	0.99	0.98	1.00	0.97	1.00
Precision	0.87	0.91	0.93	0.92	0.79	0.95
F-measure	0.65	0.93	0.88	0.95	0.83	0.94
Recall	0.68	0.94	0.84	0.96	0.79	0.91
FP rate	0.52	0.95	0.85	0.98	0.88	0.92
1D-CNN
TP rate	0.64	0.93	0.92	0.96	0.77	0.91
ROC area	0.97	0.99	0.97	1.00	0.97	0.99
Precision	0.84	0.93	0.81	0.93	0.86	0.94
F-measure	0.73	0.93	0.86	0.94	0.82	0.92
Recall	0.64	0.93	0.92	0.96	0.77	0.91
FP rate	0.00	0.02	0.04	0.01	0.01	0.01