Displaying 3 results from an estimated 3 matches for "cancdat".
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canada
2006 Apr 27
0
pamr package: pamr.adaptthresh() error rates
...1071) # support vector m/c
library(base)
library(graphics)
library(pamr)
library(bootstrap)
rm(list = ls())
gc()
makeColon <- function(){
# This dataset has 24 cancer, and 9 normal samples
n2 <- read.table("data/Colon.data",header = FALSE,sep = ",")
cancdat <- n2[,n2[1,]== 'tumor']
normdat <- n2[,n2[1,]== 'normal']
cancdat <- cancdat[-1,]
normdat <- normdat[-1,]
mat <- as.matrix(cbind(cancdat,normdat))
actclass <- rep(c(1, 2), c(ncol(cancdat), ncol(normdat)))
return(list(mat,actclass))
}...
2006 Apr 27
0
package pamr: pamr.adaptthresh() error rates
...############################# library(base) library(graphics) library(pamr) rm(list = ls()) gc() makeColon <- function(){ # This dataset has 24 cancer, and 9 normal samples n2 <- read.table("data/Colon.data",header = FALSE,sep = ",") cancdat <- n2[,n2[1,]== 'tumor'] normdat <- n2[,n2[1,]== 'normal'] cancdat <- cancdat[-1,] normdat <- normdat[-1,] mat <- as.matrix(cbind(cancdat,normdat)) actclass <- rep(c(1, 2), c(ncol(cancdat), ncol(normdat))) return(list(mat,actclass))...
2006 Apr 27
0
package pamr: pamr.adapthresh() ---- Take 2!
...1071) # support vector m/c
library(base)
library(graphics)
library(pamr)
library(bootstrap)
rm(list = ls())
gc()
makeColon <- function(){
# This dataset has 24 cancer, and 9 normal samples
n2 <- read.table("data/Colon.data",header = FALSE,sep = ",")
cancdat <- n2[,n2[1,]== 'tumor']
normdat <- n2[,n2[1,]== 'normal']
cancdat <- cancdat[-1,]
normdat <- normdat[-1,]
mat <- as.matrix(cbind(cancdat,normdat))
actclass <- rep(c(1, 2), c(ncol(cancdat), ncol(normdat)))
return(list(mat,actclass))
}...