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I'm going through the bartMachine vignette for R, and towards the end, it has an example for using bartMachine for classification problems. This is using the Pima.te data set in the MASS package. When trying to predict "type" with bartMachine (just following the vignette), it looks like my confusion matrix is labeled incorrectly, by comparing my results to the vignette's. I'm getting extremely high error rates - and the numbers in the off diagonal look an awful lot like the vignette's true positive and true negative numbers. Can anyone else confirm this?

    options(java.parameters = "-Xmx5g")
    library(bartMachine)
    set_bart_machine_num_cores(4)
    data("Pima.te",package = "MASS")
    X <- data.frame(Pima.te[,-8])
    y <- Pima.te[,8]

    bart_machine_cv <- bartMachineCV(X,y)
    bart_machine_cv
Dslans
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    Welcome to StackOverflow. Please read (1) [how do I ask a good question](http://stackoverflow.com/help/how-to-ask), (2) [How to create a MCVE](http://stackoverflow.com/help/mcve) as well as (3) [how to provide a minimal reproducible example in R](http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example#answer-5963610). Then edit and improve your question accordingly. I.e., provide input data and what lines of code you tried (incl. loading the required packages). – lukeA May 11 '16 at 21:27

1 Answers1

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It looks like there is indeed a labeling error in the package which will be fixed in the next version (1.2.3) https://github.com/kapelner/bartMachine/blob/255c206be6834d0ab13b9689a41d961de1e73d8a/bartMachine/CHANGELOG

Dslans
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