RD <- cumsum(rnorm(100000))+100


ln <- length(RD)

hankel <- function(data, r=10) {
  do.call(cbind,
          lapply(0:(r-1),function(i) { data[(i+1):(length(data)-(r-1-i))]}))} #hankel matrx
dat <- t(apply(hankel(RD), 1, function(x) scale(x,T,T)))

target <- rep(0,ln)
for(i in 11:(ln-20)){
                      
                  if(RD[i]>max(RD[(i-1):(i-10)]) && RD[i]>max(RD[(i+1):(i+20)]) ) target[i+1] <- 1
                  if(RD[i]<min(RD[(i-1):(i-10)]) && RD[i]<min(RD[(i+1):(i+20)]) ) target[i+1] <- -1
}




del <- 1:(ncol(dat)-1)
target <- as.factor(target[-del])



train <- 1:50000
test <- 50001:nrow(dat)



library(randomForest)

RF <- randomForest(target[train]~., data = dat[train,] , mtry=5 , ntree=30)
RF
plot(RF)
varImpPlot(RF)