function(dataHO, targetHO, param) {
require(rpart)
method <- ifelse(task == "classification", "class", "anova")
+ if (is.null(colnames(dataHO)))
+ colnames(dataHO) <- paste0("V", 1:ncol(dataHO))
df <- data.frame(cbind(dataHO, target=targetHO))
model <- rpart::rpart(target ~ ., df, method=method, control=list(cp=param))
- function(X) predict(model, X)
+ function(X) {
+ if (is.null(colnames(X)))
+ colnames(X) <- paste0("V", 1:ncol(X))
+ predict(model, as.data.frame(X))
+ }
}
}
else if (family == "rf") {
require(rpart)
df <- data.frame(cbind(data, target=target))
ctrl <- list(
+ cp = 0,
minsplit = 2,
minbucket = 1,
- maxcompete = 0,
- maxsurrogate = 0,
- usesurrogate = 0,
- xval = 0,
- surrogatestyle = 0,
- maxdepth = 30)
+ xval = 0)
r <- rpart(target ~ ., df, method="class", control=ctrl)
cps <- r$cptable[-1,1]
- if (length(cps) <= 11)
+ if (length(cps) <= 11) {
+ if (length(cps == 0))
+ stop("No cross-validation possible: select another model")
return (cps)
+ }
step <- (length(cps) - 1) / 10
cps[unique(round(seq(1, length(cps), step)))]
}