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netClass (version 1.2.1)

train.stsvm: Training the data using stsvm methods

Description

Training the data using stsvm methods

Usage

train.stsvm(x=x, y=y, DEBUG=FALSE,Gsub=Gsub, op.method="sp", op=10,aa=100,
			dk=dk, dk.tf=0.05,seed = 1234,Cs=10^(-3:3),EN2SY=NULL)

Arguments

x
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.
op.method
Method for selecet optimal feature subgoups: pt is permutation test, sp is span bound.
op
optimal on top op
aa
permutation test steps
dk
Random Walk Kernel matrix of network
dk.tf
cut off p-value of permutation test
seed
seed for random sampling.
Cs
Soft-margin tuning parameter of the SVM. Defaults to 10^c(-3:3).
EN2SY
A list for mapping gene sybol ids or entez ids.

Value

  • The list returned
  • trainedThe tranined models for traning folds
  • featThe feature selected by each by the train

See Also

See cv.stsvm

Examples

Run this code
#see cv.stsvm

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