Nothing
"addtest" <-
function(x,test.x,test.y,...){
if(!inherits(x,"ada")){
stop("Error: Object is not of class ada")
}
if(missing(test.y)){
stop("This funciton needs a tesing response")
}
if(missing(test.x)){
stop("This function needs testing data")
}
kapstat<-function(tab=diag(2) ){
if(dim(tab)[1]==1){
return(0)
}
if(dim(tab)[1]==dim(tab)[2]){
rs<-apply(tab,2,sum)
cs<-apply(tab,1,sum)
N<-sum(rs)
E<-sum(rs*cs)/N^2
O<-sum(diag(tab))/N
return( (O-E)/(1-E) )
}else{
return(NA)
}
}
iter=x$iter
lev=levels(as.factor(test.y))
if(length(lev)>2){
stop("Error The response must have 2 levels")
}
y=c(-1,1)[as.numeric(as.factor(test.y))]
nt<-"vector"
test.errs<-test.kaps<-rep(0,iter)
test.x=as.data.frame(test.x)
f<-x$model$lossObj$predict.type
tmp=sapply(1:iter,function(i)f(f=x$model$trees[[i]],dat=test.x))
tmp=t(t(tmp)*x$model$alpha)
Fm=rep(0,length(y))
for(m in 1:iter){
Fm<-Fm+tmp[,m]
tab<-matrix(table(sign(Fm),y),nrow=2,ncol=2)
test.errs[m]<-1-sum(diag(tab))/sum(tab)
test.kaps[m]<-1-kapstat(tab)
}
x$model$errs=cbind(x$model$errs,test.errs,test.kaps)
n1<-length(x$model$F)
x$model$F[[n1+1]]<-Fm
x
}
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