[R] Question about Rpart function

Hello, When considering linear function where dependent variable is a function of lags of dependent variables ( co-variates are kind of auto regressive).Question is .Can i take entire data set for rpart . Then split data into training and testing and validate the model for testing data.In

Re: [R] question on rpart

attached is the data set which generates the rgui.exe cpu loop... here are commands : library(rpart) train-read.csv(traindata.csv,header=T) y-as.numeric(train[,18]) x-train[,1:3] fit-rpart(y~.,x) On Thu, Apr 22, 2010 at 9:25 AM, Terry Therneau thern...@mayo.edu wrote: --- Begin included

Re: [R] question on rpart

--- Begin included message I have attempted to email the author of this package without success, just wondering if anybody else has experienced this. I am having an using rpart on 4000 rows of data with 13 attributes. I can run the same test on 300 rows of the same data with no issue. When I run

[R] question on rpart

Hello, I have attempted to email the author of this package without success, just wondering if anybody else has experienced this. I am having an using rpart on 4000 rows of data with 13 attributes. I can run the same test on 300 rows of the same data with no issue. When I run on 4000 rows,

Re: [R] Question about rpart decision trees (being used to predict customer churn)

Hello, Isn't it totally counter-intuitive that if you penalize the error less the tree finds it? See: experience - as.factor(c(rep(good,90), rep(bad,10))) cancel - as.factor(c(rep(no,85), rep(yes,5), rep(no,5),rep(yes,5))) foo - function( i ){ tmp - rpart(cancel ~ experience,

Re: [R] Question about rpart decision trees (being used to predict customer churn)

Hello, If you do my.tree - rpart(cancel ~ experience) and then you check my.tree$frame you will note that the complexity parameter there is 0. Check ?rpart.object to get a description of what this output means. But essentially, you will not be able to break the leaf unless you set a

Re: [R] Question about rpart decision trees (being used to predict customer churn)

2009/7/27 Robert Smith robertpsmith2...@gmail.com Hi, I am using rpart decision trees to analyze customer churn. I am finding that the decision trees created are not effective because they are not able to recognize factors that influence churn. I have created an example situation below.

[R] Question about rpart decision trees (being used to predict customer churn)

-- begin included message --- Hi, I am using rpart decision trees to analyze customer churn. I am finding that the decision trees created are not effective because they are not able to recognize factors that influence churn. I have created an example situation below. What do I need to do to for

[R] Question about rpart decision trees (being used to predict customer churn)

Hi, I am using rpart decision trees to analyze customer churn. I am finding that the decision trees created are not effective because they are not able to recognize factors that influence churn. I have created an example situation below. What do I need to do to for rpart to build a tree with the

[R] Question about rpart(sth~.,database)

I have a standard database - HouseVotes84 For example: Class V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12 V13 V14 V15 V16 1 republicann y ny y y n n n y NA y y y ny 2 republicann y ny y y n n n nn y y y n NA 3 democrat NA y y NA

Re: [R] Question about rpart(sth~.,database)

Grześ wrote: I have a standard database - HouseVotes84 For example: Class V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12 V13 V14 V15 V16 1 republicann y ny y y n n n y NA y y y ny 2 republicann y ny y y n n n nn y y y n NA 3

Re: [R] Question about rpart(sth~.,database)

Gavin Simpson wrote: Grześ wrote: I have a standard database - HouseVotes84 For example: Class V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12 V13 V14 V15 V16 1 republicann y ny y y n n n y NA y y y ny 2 republicann y ny y y n n n nn