R/print.ada.R

In ada: The R Package Ada for Stochastic Boosting

"print.ada" <-
function(x,...){
  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)
    }
  }
  if(!is.null(cl <- x$call)) {
    names(cl)[2] <- ""
    cat("Call:\n")
    dput(cl)
  }
  
  g=x$fit
  tab=x$confusion
  errm=1-sum(diag(tab))/length(x$actual)
  
  cat("\nLoss:", x$model$lossObj$loss,"Method:", x$model$lossObj$type,"\  Iteration:", x$iter,"\n")
  cat("\nFinal Confusion Matrix for Data:\n")
  print(tab)
  cat("\nTrain Error:", round(errm, digits=3),"\n")
  if(x$iter<=5){
    j<-which.min(x$model$oob.str$oobm.err)
  }else{
    j<-which.min(x$model$oob.str$oobm.err[-c(1:5)])+5
  }
  cat("\nOut-Of-Bag Error: ",round(x$model$oob.str$oobm.err[j],3)," iteration=",j,"\n")
  cat("\nAdditional Estimates of number of iterations:\n\n")
  errs<-as.data.frame(x$model$errs)
  k<-dim(errs)[2]/2
  names(errs)<-paste(names(errs),sort(c(1:k,1:k)),sep="")
  est.m<-apply(errs,2,which.min)
  print(est.m)
  cat("\n")
  invisible(x)
}