Re: [R] rpart - predict terminal nodes for new observations

2012-05-18 Thread tudor
Hi Uwe:

Thanks a lot for your reply.  

I contemplated the use of the predict() function but realized that it could
not return what I needed (i.e., the terminal nodes and not the classes). I
went back to the post of Professor Ripley
(http://tolstoy.newcastle.edu.au/R/e4/help/08/07/17702.html) and did find a
way to get the terminal nodes.  I am showing this approach below in case
other useRs face a similar problem.

Many thanks.

Tudor


nodes  - rpart:::pred.rpart(tree.prune,rpart:::rpart.matrix(es))
where 
tree.prune is the rpart object and es is the estimation data set.

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Re: [R] rpart - predict terminal nodes for new observations

2012-05-16 Thread Uwe Ligges



On 15.05.2012 16:30, tudor wrote:

Dear useRs:

Is there a way I could predict the terminal node associated with a new data
entry in an rpart environment? In the example below, if I had a new data
entry with an AM of 5, I would like to link it to the terminal node 2. My
searches led to http://tolstoy.newcastle.edu.au/R/e4/help/08/07/17702.html
but I do not seem to be able to operationalize Professor Ripley's
suggestions.



Use the predict() function.

Uwe Ligges



Many thanks.

Tudor


tree.prune

n= 2400

node), split, n, loss, yval, (yprob)
   * denotes terminal node

1) root 2400 779 0 (0.6754167 0.3245833)
   2) AM  6.5 1428 254 0 (0.8221289 0.1778711) *
   3) AM=6.5 972 447 1 (0.4598765 0.5401235)
 6) P=10.39666 390  86 0 (0.7794872 0.2205128) *
 7) P  10.39666 582 143 1 (0.2457045 0.7542955) *


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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
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[R] rpart - predict terminal nodes for new observations

2012-05-15 Thread tudor
Dear useRs:

Is there a way I could predict the terminal node associated with a new data
entry in an rpart environment? In the example below, if I had a new data
entry with an AM of 5, I would like to link it to the terminal node 2. My
searches led to http://tolstoy.newcastle.edu.au/R/e4/help/08/07/17702.html
but I do not seem to be able to operationalize Professor Ripley's
suggestions.

Many thanks.

Tudor

 tree.prune
n= 2400 

node), split, n, loss, yval, (yprob)
  * denotes terminal node

1) root 2400 779 0 (0.6754167 0.3245833)  
  2) AM 6.5 1428 254 0 (0.8221289 0.1778711) *
  3) AM=6.5 972 447 1 (0.4598765 0.5401235)  
6) P=10.39666 390  86 0 (0.7794872 0.2205128) *
7) P 10.39666 582 143 1 (0.2457045 0.7542955) *


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http://r.789695.n4.nabble.com/rpart-predict-terminal-nodes-for-new-observations-tp4630104.html
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R-help@r-project.org mailing list
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.