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normalizeFeatures.R
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normalizeFeatures.R
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###path
mypath<-"C:/Users/ildefons/vrije/ildefons"
###############normal-1
fname<-file.path(mypath,"featuresn1plus22.RData")
load(fname)
myl<-score2.extended.n1
mym<-con.matrix.n1
feas<-cbind(as.vector(myl[[2]]) )
myseq<-seq(4,length(myl),2)
for(i in myseq) {
feas<-cbind( feas,
as.vector(myl[[i]]) )
}
M<-1000
mym.sim<-mym
for(i in 1:(M-1)){
for(j in (i+1):M) {
if( mym.sim[i,j]==1 ||
mym.sim[j,i]==1) {
mym.sim[i,j]=1
mym.sim[j,i]=1
}
}
}
feas<-cbind( feas, as.vector(mym),as.vector(mym.sim) )
all<-feas
train.norm<-(all[,1]-mean(all[,1]))/sd(all[,1])
for(i in 2:(ncol(all)-2)) {
train.norm<-cbind(train.norm, (all[,i]-mean(all[,i]))/sd(all[,i]))
}
train.norm<-cbind(train.norm, all[,ncol(all)-1],all[,ncol(all)])
n1.norm<-train.norm
fname<-file.path(mypath,"n1norm.RData")
save(n1.norm,file=fname)
###############normal-2
fname<-file.path(mypath,"featuresn2plus22.RData")
load(fname)
myl<-score2.extended.n1
mym<-con.matrix.n1
feas<-cbind(as.vector(myl[[2]]) )
myseq<-seq(4,length(myl),2)
for(i in myseq) {
feas<-cbind( feas,
as.vector(myl[[i]]) )
}
M<-1000
mym.sim<-mym
for(i in 1:(M-1)){
for(j in (i+1):M) {
if( mym.sim[i,j]==1 ||
mym.sim[j,i]==1) {
mym.sim[i,j]=1
mym.sim[j,i]=1
}
}
}
feas<-cbind( feas, as.vector(mym),as.vector(mym.sim) )
all<-feas
train.norm<-(all[,1]-mean(all[,1]))/sd(all[,1])
for(i in 2:(ncol(all)-2)) {
train.norm<-cbind(train.norm, (all[,i]-mean(all[,i]))/sd(all[,i]))
}
train.norm<-cbind(train.norm, all[,ncol(all)-1],all[,ncol(all)])
n2.norm<-train.norm
fname<-file.path(mypath,"n2norm.RData")
save(n2.norm,file=fname)
###################valid
fname<-file.path(mypath,"featuresvalidplus22.RData")
load(fname)
myl<-score2.extended.valid
con.matrix.valid<-matrix(nrow=1000,ncol=1000)
con.matrix.valid[]<-0
mym<-con.matrix.valid
feas<-cbind(as.vector(myl[[2]]) )
myseq<-seq(4,length(myl),2)
for(i in myseq) {
feas<-cbind( feas,
as.vector(myl[[i]]) )
}
M<-1000
mym.sim<-mym
for(i in 1:(M-1)){
for(j in (i+1):M) {
if( mym.sim[i,j]==1 ||
mym.sim[j,i]==1) {
mym.sim[i,j]=1
mym.sim[j,i]=1
}
}
}
feas<-cbind( feas, as.vector(mym),as.vector(mym.sim) )
all<-feas
train.norm<-(all[,1]-mean(all[,1]))/sd(all[,1])
for(i in 2:(ncol(all)-2)) {
train.norm<-cbind(train.norm, (all[,i]-mean(all[,i]))/sd(all[,i]))
}
train.norm<-cbind(train.norm, all[,ncol(all)-1],all[,ncol(all)])
valid.norm<-train.norm
fname<-file.path(mypath,"validnorm.RData")
save(valid.norm,file=fname)
###################test
fname<-file.path(mypath,"featurestestplus22.RData")
load(fname)
myl<-score2.extended.test
con.matrix.test<-matrix(nrow=1000,ncol=1000)
con.matrix.test[]<-0
mym<-con.matrix.test
feas<-cbind(as.vector(myl[[2]]) )
myseq<-seq(4,length(myl),2)
for(i in myseq) {
feas<-cbind( feas,
as.vector(myl[[i]]) )
}
M<-1000
mym.sim<-mym
for(i in 1:(M-1)){
for(j in (i+1):M) {
if( mym.sim[i,j]==1 ||
mym.sim[j,i]==1) {
mym.sim[i,j]=1
mym.sim[j,i]=1
}
}
}
feas<-cbind( feas, as.vector(mym),as.vector(mym.sim) )
all<-feas
train.norm<-(all[,1]-mean(all[,1]))/sd(all[,1])
for(i in 2:(ncol(all)-2)) {
train.norm<-cbind(train.norm, (all[,i]-mean(all[,i]))/sd(all[,i]))
}
train.norm<-cbind(train.norm, all[,ncol(all)-1],all[,ncol(all)])
test.norm<-train.norm
fname<-file.path(mypath,"testnorm.RData")
save(test.norm,file=fname)