R: Plot outcome predictions from superpc

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 1.09 Index]