imp20000 {RFlocalfdr}

20000 importance values

Description

A dataset containing 20000 importance values

Usage

imp20000

Format

A vector varaible importances with 20000 values

imp1

importances

Examples

require(ranger)
inv.logit <-function (x) {
    plogis(x)}

make_data <- function(nVars, nSamples) {
    as.matrix(sapply(1:nVars, function(t){sample(0:2, nSamples, replace=TRUE)}))
}

make_cont_response <- function(X, w) {
    (X-1) %*% w 
}

make_response <- function(X, w) {
   as.factor(inv.logit((X-1) %*% w * 2 ) > runif(nrow(X)))
} 


nVars <-   20000
nSamples <- 1000

set.seed(19)
X<- make_data(nVars,nSamples)

w <- rep(0, times = nVars)
w[101] <- 1
w[102] <- 1/sqrt(2)
w[103] <- 1/sqrt(4)
w[104] <- 1/sqrt(8)
w[105] <- 1/sqrt(16)
y <- make_response(X, w)


colnames(X) <- c(make.names(1:20000))
set.seed(19)
rf1<-ranger::ranger(y=y,x=X, num.trees = 2000,importance="impurity")
table(y,predict(rf1,data=X)$predictions)
#OOB prediction error:             41.30 % 
table(y,predict(rf1,data=X)$predictions)

t2 <-count_variables(rf1)
head(t2)
dim(t2)

imp<-rf1$variable.importance
imp<-log(imp)
plot(density((imp)))
hist(imp,col=6,lwd=2,breaks=100,main="histogram of importances")

res.temp <- determine_cutoff(imp, t2 ,cutoff=c(0,1,2,3),plot=c(0,1,2,3),Q=0.75,try.counter=1)
plot(c(0,1,2,3),res.temp[,3])
imp<-imp[t2 > 1]
qq <- plotQ(imp,debug.flag = 0)
ppp<-run.it.importances(qq,imp,debug=0)
aa<-significant.genes(ppp,imp,cutoff=0.2,debug.flag=0,do.plot=2, use_95_q=TRUE)
length(aa$probabilities)
names(aa$probabilities)
#' #[1] "X101"   "X102"   "X103"   "X104"   "X105"   "X2994"  "X9365"  "X10718"
# [9] "X13371" "X15517" "X16460"

counts<-t2
imp20000 <- list(imp,counts)
names(imp20000) <-c("importances","counts")