Displaying 1 result from an estimated 1 matches for "nparaminit".
2011 Jan 05
0
Nnet and AIC: selection of a parsimonious parameterisation
...2) +
alpha* sum((truth[ri == i] - predict(nn.tmp, data[ri ==
i,]))^2)
if (RSS.tmp<RSS){ RSS=RSS.tmp; nn=nn.tmp; ii=i}
}
}
if (optimFlag) {
return(RSS)
}else{
prn=nnWtsPrunning(nn,data,alpha,ii)
list(choice=prn$choice,nparam=prn$nparam,nparaminit=length(nn$wts),AIC=prn$AIC,nn1=prn$nn)
}
}
maxSize=maxSize+1; j=1;
choice <- numeric(maxSize); nparam <- numeric(maxSize); lambdaj <-
numeric(maxSize)
AIC <- numeric(maxSize); nparamInit <- numeric(maxSize)
ri <- sample(nifold, nrow(data), replace = TRUE)...