superpc.predictionplot {superpc}R Documentation

Plot outcome predictions from superpc

Description

Plots outcome predictions from superpc

Usage

superpc.predictionplot(train.obj, data, data.test,  threshold, n.components=3,
  n.class=2, shrinkage=NULL,  call.win.metafile=FALSE)
 

Arguments

train.obj Object returned by superpc.train
data List of training data, of form described in superpc.train documen tation,
data.test List of test data; same form as training data
threshold Threshold for scores: features with abs(score)>threshold are retained.
n.components Number of principal components to compute. Should be 1,2 or 3.
n.class Number of classes for survival stratification. Onply applicable for survival data. Default 2.
shrinkage Shrinkage to be applied to feature loadings. Default is NULL meaning no shrinkage
call.win.metafile Used only by Excel interface call to function

Author(s)

Eric Bair and Robert Tibshirani

Examples

set.seed(332)
x<-matrix(rnorm(1000*40),ncol=40)
y<-10+svd(x[1:60,])$v[,1]+ .1*rnorm(40)
censoring.status<- sample(c(rep(1,30),rep(0,10)))

featurenames <- paste("feature",as.character(1:1000),sep="")
data<-list(x=x,y=y, censoring.status=censoring.status, featurenames=featurenames)

a<- superpc.train(data, type="survival")

superpc.predictionplot(a,data,data,threshold=1)


[Package superpc version 1.05 Index]