Oral cancer prognosis based on clinicopathologic and genomic markers using a hybrid of feature selection and machine learning methods

Table 5 Classification accuracy and AUC for group 1

Feature selection	3-input		4-input		5-input		6-input		7-input
Feature selection	%	AUC	%	AUC	%	AUC	%	AUC	%	AUC
ANFIS
GA	70.95	0.66	67.42	0.61	64.76	0.63	58.57	0.55	57.62	0.54
CC	58.10	0.53	74.76	0.70	51.43	0.43	57.62	0.50	64.29	0.58
ReliefF	61.43	0.53	50.59	0.50	58.10	0.50	64.29	0.54	64.29	0.54
CC-GA	44.76	0.44	67.62	0.57	63.81	0.55	64.29	0.54	57.62	0.52
ReliefF-GA	67.14	0.55	60.48	0.59	67.62	0.59	51.90	0.47	64.76	0.57
ANN
GA	45.52	0.53	52.43	0.53	45.05	0.47	48.38	0.52	45.33	0.50
CC	54.48	0.61	53.57	0.59	51.29	0.58	51.29	0.51	52.33	0.53
ReliefF	51.52	0.48	41.62	0.47	46.05	0.49	46.05	0.48	44.10	0.48
CC-GA	49.24	0.51	49.48	0.52	46.67	0.49	48.29	0.49	50.48	0.51
ReliefF-GA	50.24	0.55	52.86	0.59	56.76	0.58	47.00	0.51	50.05	0.54
SVM
GA	60.95	0.53	61.43	0.51	58.10	0.48	58.10	0.46	61.43	0.49
CC	60.95	0.53	60.95	0.53	58.10	0.46	51.43	0.41	51.43	0.41
ReliefF	54.29	0.44	50.95	0.42	51.43	0.42	48.10	0.40	50.95	0.45
CC-GA	63.81	0.55	61.43	0.51	58.10	0.46	58.10	0.48	58.10	0.49
ReliefF-GA	64.29	0.50	64.29	0.50	64.29	0.50	64.29	0.50	54.76	0.46
LR
GA	64.29	0.56	67.62	0.60	64.76	0.55	68.10	0.64	64.29	0.60
CC	64.29	0.56	60.48	0.57	67.62	0.61	67.62	0.61	64.29	0.58
ReliefF	50.59	0.44	50.59	0.44	48.10	0.39	41.43	0.34	44.29	0.39
CC-GA	67.62	0.57	67.62	0.60	61.43	0.51	70.95	0.72	64.76	0.67
ReliefF-GA	54.29	0.54	51.43	0.52	61.43	0.62	47.62	0.55	48.10	0.51

ISSN: 1471-2105