pamr.cv {pamr} | R Documentation |
A function to cross-validate the nearest shrunken centroid classifier produced by pamr.train
pamr.cv(fit, data, nfold = min(table(data$y)), folds = balanced.folds(data$y), ...)
fit |
The result of a call to pamr.train |
data |
A list with at least two components: x- an expression genes in the rows, samples in the columns, and y- a vector of the class labels for each sample. Same form as data object used by pamr.train. |
nfold |
Number of cross-validation folds. Default is the smallest class size |
folds |
A list with nfold components, each component a vector of indices of the samples in that fold. By default a (random) balanced cross-validation is used |
... |
{Any additional arguments that are to be passed to pamr.train}
pamr.cv
carries out cross-validation for a nearest shrunken
centroid classifier.
A list with components
threshold |
|
errors |
The number of cross-validation errors for each threshold value |
loglik |
The cross-validated multinomial log-likelihood value for each threshold value |
size |
A vector of the number of genes that survived the thresholding, for each threshold value tried. |
yhat |
A matrix of size n by nthreshold, containing the cross-validated class predictions for each threshold value, in each column |
prob |
A matrix of size n by nthreshold, containing the cross-validated class probabilities for each threshold value, in each column |
folds |
The cross-validation folds used |
call |
The calling sequence used |
Trevor Hastie,Robert Tibshirani, Balasubramanian Narasimhan, and Gilbert Chu
set.seed(120) x <- matrix(rnorm(1000*20),ncol=20) y <- sample(c(1:4),size=20,replace=TRUE) mydata <- list(x=x,y=y) mytrain <- pamr.train(mydata) mycv <- pamr.cv(mytrain,mydata)