Dear mailing list, I am using the cforest() method from the party package to train a randomForest with ten input parameters which sometimes contain "NA"s. The predicted variable is a binary decision. Building the tree works fine without warnings or error messages, but when using the predict() statement for validation, I run in an error:
forest <- cforest(V31 ~ V1+V2+V3, data=training) prediction <- predict(forest, testset) "Error in OOB && is.null(newdata) : invalid 'x' type in 'x && y'" On the other hand: Creating a tree, using the ctree() method and validating the prediction using the predict() method works fine: tree <- ctree(V31 ~ V1+V2+V3, data=training) prediction <- predict(tree, testset) "training" and "testset" are sampled from the same data.frame. Does anyone has an explanation for this behavior? I would like to test if cforest() outperforms ctree()! Thank you for your help! Florian Kiefer ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
