Eric Rodriguez wrote:
Hi,
I would like to break a dataset in n.classes quantiles.
Till now, I used the following code:
Classify.Quantile <- function (dataset, nclasses = 10)
{
n.probs <- seq(0,1,length=nclasses+1)
n.labels = paste("C", 1:nclasses-1, sep="")
n.rows <- nrow(dataset)
n.cols <- ncol(dataset)
n.motif <- dataset
for (j in 2:n.cols)
{
cat(j, " ");
discr = n.labels[unclass(cut(dataset[,j],quantile(dataset[,j],n.probs),include.lowest=T))]
n.motif[,j] = discr
}
res <- list(motif=n.motif, labels=n.labels, n.classes=nclasses)
return(res)
}
but if you try to call this with a dataset with a lot of same value, you got a
Error in cut.default(dataset[, j], quantile(dataset[, j], n.probs),
include.lowest = T) :
cut: breaks are not unique
I perfectly understand why but I would like to know how to avoid this behaviour.
for e.g., use this code to raise the error:
x=matrix(0,1000,1)
x[100]=1
Classify.Quantile(x, 10)
of course this dataset is a bit extreme but it happens to get data
with very small variance.
Thanks for any help you could provide
The cut2 function in the Hmisc package may help. -FH
--
Frank E Harrell Jr Professor and Chair School of Medicine
Department of Biostatistics Vanderbilt University
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