I know that some ICD9 codes contain letters, so I suspect that they
are stored as "character". Here is a function that just pads zeros
on to the end to make the string five characters long.
format <- function(icd9) {
len <- length(strsplit(icd9, "")[[1]])
pad <- ""
if (num <- 5-len)
pad
Claudia,
Can you send us the actual call you are making to rpart()?
The call to plot() doesn't really help.
Darin
On Wed, Feb 28, 2007 at 11:53:45AM -0500, Wensui Liu wrote:
> with seeing more code and output, i guess your tree fails to grow.
>
> On 2/28/07, Claudia Romero <[EMAIL PROTECTED]> wro
Amy,
I have also had this issue with randomForest, that is, you lose the
ability to explain the classifier in a simple way to
non-specialists (everyone can understand the single decision tree.)
As far as comparing the accuracy of the two, I think that you are
correct in comparing them by the actua
> If there is a way around that with randomForest, I'd be interested to
> know too.
>
> Hugues Sicotte
>
>
> -Original Message-
> From: [EMAIL PROTECTED]
> [mailto:[EMAIL PROTECTED] On Behalf Of Darin A. England
> Sent: Thursday, January 04, 2007 3:
Does anyone know a reason why, in principle, a call to randomForest
cannot accept a data frame with missing predictor values? If each
individual tree is built using CART, then it seems like this
should be possible. (I understand that one may impute missing values
using rfImpute or some other metho
