Nothing
# split_node <- function(X,Y,m_feature,Index,i,model,min_leaf,Inv_Cov_Y,Command){
# ii=NULL
# Index_left=NULL
# Index_right=NULL
# if(length(Index)>min_leaf){ #create problem with 2
# ff2 = ncol(X) # number of features
# ff =sort(sample(ff2, m_feature)) #randomly taken 10 features, for each splits vary
# Result = splitt(X,Y,m_feature,Index,Inv_Cov_Y,Command, ff)
# Index_left=Result[[1]]
# Index_right=Result[[2]]
# if(i==1){
# Result[[5]]=c(2,3)
# }else{
# j=1
# while (length(model[[j]])!=0){
# j=j+1
# }
# Result[[5]]=c(j,j+1)
# }
#
# model[[i]]=Result
# k=i
# i=1 #maybe unnecessary
# while (length(model[[i]])!=0){
# i=i+1
# }
# model[[Result[[5]][1]]]=Result[[1]]
# model[[Result[[5]][2]]]=Result[[2]]
#
# model=split_node(X,Y,m_feature,Index_left,model[[k]][[5]][1],model,min_leaf,Inv_Cov_Y,Command)
#
# model=split_node(X,Y,m_feature,Index_right,model[[k]][[5]][2],model,min_leaf,Inv_Cov_Y,Command)
#
#
# }else{
# ii[[1]]=matrix(Y[Index,],ncol=ncol(Y))
# model[[i]]=ii
# }
#
#
# return(model)
# }
split_node <- function(X,Y,m_feature,Index,i,model,min_leaf,Inv_Cov_Y,Command){
ii=NULL
Index_left=NULL
Index_right=NULL
if(length(Index)>min_leaf){
ff2 = ncol(X) # number of features
ff =sort(sample(ff2, m_feature)) #randomly taken m_feature features, for each splits vary
# Result = splitt(X,Y,m_feature,Index,Inv_Cov_Y,Command, ff)
Result = MultivariateRandomForest::splitt2(X,Y,m_feature,Index,Inv_Cov_Y,Command, ff)
Index_left=Result[[1]]
Index_right=Result[[2]]
if(i==1){
Result[[5]]=c(2,3)
}else{
j=1
while (length(model[[j]])!=0){
j=j+1
}
Result[[5]]=c(j,j+1)
}
model[[i]]=Result
k=i
i=1 #maybe unnecessary
while (length(model[[i]])!=0){
i=i+1
}
model[[Result[[5]][1]]]=Result[[1]]
model[[Result[[5]][2]]]=Result[[2]]
model=split_node(X,Y,m_feature,Index_left,model[[k]][[5]][1],model,min_leaf,Inv_Cov_Y,Command)
model=split_node(X,Y,m_feature,Index_right,model[[k]][[5]][2],model,min_leaf,Inv_Cov_Y,Command)
}else{
ii[[1]]=matrix(Y[Index,],ncol=ncol(Y))
model[[i]]=ii
}
return(model)
}
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