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Jin Zhu
You can install the released version of cdcsis from CRAN with:
install.packages("cdcsis")
This is a basic example which shows you how to pick out the important feature from high-dimensional dataset:
library(cdcsis)
set.seed(1)
<- 100
num <- 1000
p <- matrix(rnorm(num * p), nrow = num, ncol = p)
x <- rnorm(num)
z <- 3*x[, 1] + 1.5*x[, 2] + 4*z*x[, 5] + rnorm(num)
y <- cdcsis(x, y, z)
res head(res[["ix"]], n = 10)
cdcsis function successfully selects the informative variables from 1000 features pool.
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GPL (>= 2)
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