Identifying the Gene Signatures from Gene-Pathway Bipartite Network Guarantees the Robust Model Performance on Predicting the Cancer Prognosis

Table 4

The results of predicting the molecular subclasses of high-grade glioblastoma in original and swap analyses.

		Our model
		SP	SE	ACC	MCC	AUC
Original analysis	Training	0.900	0.900	0.900	0.800	0.900
	Validation	0.750	1.000	0.875	0.775	0.875
Swap analysis	Training	0.950	0.900	0.925	0.851	0.925
	Validation	0.800	0.567	0.683	0.377	0.684

In the prediction, the gene expression profile termed ProNeural (PN) was defined as positive sample.
AUC represented the area under the ROC curve.
See notes under Table 2 for more information.