Nothing
print.MCRestimate <- function(x,...)
{ class.function <- x$class.method
type.of.cv <- ifelse(x$cross.outer==length(x$classes),"leave-one-out",paste(x$cross.outer,"-fold",sep=""))
one.or.many <- ifelse(x$cross.repeat==1,paste(x$cross.repeat,"repetition of"),paste(x$cross.repeat,"repetitions of"))
thePres <- x$thePreprocessingMethods
thePres <- thePres[thePres!="identity"]
nP <- length(thePres)
cat("\n")
cat("Result of MCRestimate with", one.or.many,type.of.cv,"cross-validation",fill=TRUE)
if( "block.column" %in% names(x) ){
if( !is.null(x$block.column) ) cat(" on blocks defined by covariate :",x$block.column,":")
}
if( "stratify" %in% names(x) ){
if( x$stratify ) cat(" using balanced folds (stratify==TRUE) ")
}
cat("\n")
if(nP>0){
for (i in 1:nP) cat(paste("Preprocessing function",i,":",thePres[i]),"\n")
} else
cat("No preprocessing \n")
cat( "Classification function : ", x$class.method, "\n\n",
"The confusion table: \n",sep="",...)
print(round(x$table,3), ...)
}
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