train.hubc: Predicting the data using hub nodes classification model
In netClass: netClass: An R Package for Network-Based Biomarker Discovery

Predicting the data using hub nodes classification model

1 2	train.hubc(x = x, y = y, DEBUG = FALSE, Gsub = Gsub, gHub = gHub, hubs = hubs, nperm = 500, node.ct = 0.95, Cs = 10^(-3:3))

`x`	gene expression data for training.
`y`	Class labels
`DEBUG`	show debugging information in screen more or less.
`Gsub`	an adjacency matrix that represents the underlying biological network.
`gHub`	Subgraph of hubs of graph Gs
`hubs`	Hubs in graph Gs
`nperm`	number of permutation test steps
`node.ct`	cut off value for select highly quantile nodes in a nwtwork. Defaults to `0.98)`.
`Cs`	Soft-margin tuning parameter of the SVM. Defaults to `10^c(-3:3)`.