ps.cluster {genefu} | R Documentation

## Function to compute the prediction strength of a clustering model

### Description

This function computes the prediction strength of a clustering model as published in R. Tibshirani and G. Walther 2005.

### Usage

    ps.cluster(cl.tr, cl.ts, na.rm = FALSE)

### Arguments

`cl.tr` | Clusters membership as defined by the original clustering model, i.e. the one that was not fitted on the dataset of interest.
`cl.ts` | Clusters membership as defined by the clustering model fitted on the dataset of interest.
`na.rm` | `TRUE` if missing values should be removed, `FALSE` otherwise.

### Value

`ps` | the overall prediction strength (minimum of the prediction strengths at cluster level).
`ps.cluster` | Prediction strength for each cluster
`ps.individual` | Prediction strength for each sample.

### Author(s)

Benjamin Haibe-Kains

### References

R. Tibshirani and G. Walther (2005) "Cluster Validation by Prediction Strength", Journal of Computational and Graphical Statistics, 14(3):511–528.

### Examples

    ## load SSP signature published in Sorlie et al. 2003
    data(ssp2003)
    ## load NKI data
    data(nkis)
    ## SP2003 fitted on NKI
    ssp2003.2nkis <- intrinsic.cluster(data=data.nkis, annot=annot.nkis,
      do.mapping=TRUE, std="robust",
      intrinsicg=ssp2003$centroids.map[ ,c("probe", "EntrezGene.ID")],
      number.cluster=5, mins=5, method.cor="spearman",
      method.centroids="mean", verbose=TRUE)
    ## SP2003 published in Sorlie et al 2003 and applied in VDX
    ssp2003.nkis <- intrinsic.cluster.predict(sbt.model=ssp2003,
      data=data.nkis, annot=annot.nkis, do.mapping=TRUE, verbose=TRUE)
    ## prediction strength of sp2003 clustering model
    ps.cluster(cl.tr=ssp2003.2nkis$subtype, cl.ts=ssp2003.nkis$subtype,
      na.rm = FALSE)

[Package genefu version 2.19.1 Index]