Pathway-Based Feature Selection Algorithm for Cancer Microarray Data

Table 2

Accuracy of our algorithm obtained from Cross Validation experiments on real pathway. Feature set obtained from one data set is tested against another data set. We always chose target data from the same class of microarray in order to avert cross platform problems. The cross validation results implies that the feature set generated by BPFS provides satisfactory performance in cross data sets without significant loss of accuracy. We also compare our method with a trimmed version where we skip step 3.3. The complete version of the algorithm (with pathway) is indicated by 1 at the superscript while the trimmed version (without pathway) is denoted by the superscript 2.

Dataset used	Dataset used to	Number of Features
for testing	extract the features	5	10	20	40	60	80	100	120	140
	BCR^1	0.65	0.65	0.72	0.72	0.73	0.75	0.74	0.74	0.73
BCR	CCR^1	0.63	0.61	0.61	0.63	0.66	0.68	0.66	0.71	0.69
	CCR^2	0.64	0.62	0.65	0.63	0.64	0.65	0.66	0.65	0.68
	Lancet^1	0.57	0.59	0.58	0.63	0.61	0.61	0.65	0.65	0.67
	Lancet^2	0.55	0.55	0.63	0.62	0.58	0.64	0.66	0.69	0.7
	70-Gene-Sig^1	0.62	0.59	0.59	0.66	0.67	0.68	0.70	0.73	0.71
	CCR^1	0.70	0.70	0.72	0.73	0.77	0.77	0.76	0.77	0.78
CCR	BCR^1	0.60	0.63	0.67	0.65	0.65	0.66	0.68	0.66	0.66
	BCR^2	0.53	0.65	0.65	0.66	0.61	0.67	0.69	0.68	0.65
	Lancet^1	0.57	0.58	0.62	0.60	0.66	0.69	0.68	0.70	0.71
	Lancet^2	0.58	0.58	0.61	0.65	0.68	0.73	0.78	0.75	0.75
	70-Gene-Sig^1	0.53	0.52	0.51	0.55	0.65	0.66	0.66	0.66	0.64
	Lancet^1	0.58	0.58	0.61	0.61	0.62	0.62	0.62	0.64	0.63
	BCR^1	0.54	0.57	0.54	0.56	0.55	0.56	0.59	0.60	0.63
Lancet	BCR^2	0.55	0.59	0.57	0.55	0.56	0.55	0.54	0.57	0.53
	CCR^1	0.55	0.56	0.54	0.55	0.59	0.56	0.59	0.58	0.59
	CCR^2	0.61	0.62	0.64	0.56	0.61	0.60	0.60	0.60	0.59
	70-Gene-Sig^1	0.56	0.55	0.53	0.57	0.58	0.60	0.57	0.61	0.61
Nature	Nature^1	0.68	0.65	0.65	0.65	0.72	0.70	0.72	0.70	0.66
	JNCI^1	0.71	0.71	0.65	0.61	0.59	0.64	0.60	0.57	0.61
	JNCI^2	0.67	0.70	0.63	0.60	0.66	0.74	0.73	0.74	0.72