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library("sampling")
library("gam")
nominal_to_binary <- function( orig_data )
{
data = as.data.frame( orig_data )
result = NULL
for (i in 1:ncol(data))
{
#print(i)
if (is.numeric( data[,i] ) )
{
if (is.null(result))
result = data.frame(data[,i])
else
result = data.frame(result, data[,i])
colnames(result)[ncol(result)] <- colnames(data)[i]
}
else
{
vals = unique(data[,i])
for (j in 1:length(vals))
{
#print(j)
bins = c()
for (k in 1:nrow(data))
{
if(data[,i][k] == vals[j])
bins = c(bins,1)
else
bins = c(bins,0)
}
#print(bins)
if (is.null(result))
result = data.frame(bins)
else
result = data.frame(result, bins)
colnames(result)[ncol(result)] <- paste(colnames(data)[i],"is",vals[j])
if (length(vals)==2) break
}
}
}
result
}
process_data <- function( data )
{
if (!is.numeric(data))
data.num = nominal_to_binary(data)
else
data.num = data
if(any(is.na(data.num)))
data.repl = na.gam.replace(data.num)
else
data.repl = data.num
data.repl
}
stratified_split <- function( data, ratio=0.3 )
{
data.processed = as.matrix(process_data( data ))
pik = rep(ratio,times=nrow(data.processed))
data.strat = cbind(pik,data.processed)
samplecube(data.strat,pik,order=2,comment=F)
}
stratified_k_fold_split <- function( data, num_folds=10 )
{
print(paste(num_folds,"-fold-split, data-size",nrow(data)))
data.processed = as.matrix(process_data( data ))
folds = rep(0, times=nrow(data))
for (i in 1:(num_folds-1))
{
prop = 1/(num_folds-(i-1))
print(paste("fold",i,"/",num_folds," prop",prop))
pik = rep(prop,times=nrow(data))
for (j in 1:nrow(data))
if(folds[j]!=0)
pik[j]=0
data.strat = cbind(pik,data.processed)
s<-samplecube(data.strat,pik,order=2,comment=F)
print(paste("fold size: ",sum(s)))
for (j in 1:nrow(data))
if (s[j] == 1)
folds[j]=i
}
for (j in 1:nrow(data))
if (folds[j] == 0)
folds[j]=num_folds
folds
}
plot_split <- function( data, split )
{
data.processed = process_data( data )
data.pca <- prcomp(data.processed, scale=TRUE)
data.2d =as.data.frame(data.pca$x)[1:2]
plot( NULL,
xlim = extendrange(data.2d[,1]), ylim = extendrange(data.2d[,2]),
xlab = "pc 1", ylab = "pc 2")
for (j in 0:max(split))
{
set = c()
for (i in 1:nrow(data))
if (split[i] == j)
set = c(set,i)
points(data.2d[set,], pch = 2, col=(j+1))
}
}
#a<-matrix(rnorm(100, mean=50, sd=4), ncol=5)
#b<-matrix(rnorm(5000, mean=0, sd=10), ncol=5)
#data<-rbind(a,b)
#c<-matrix(rnorm(50, mean=-50, sd=2), ncol=5)
#data<-rbind(data,c)
#data=iris
#split = stratified_k_fold_split(data, num_folds=3)
#split = stratified_split(data, ratio=0.3)
#plot_split(data,split)
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