Hi Ajit,
Please send the code you are running in each case.

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On Fri, Nov 4, 2011 at 8:36 AM, aajit75 <aajit75@yahoo.co.in> wrote:

> Hi Experts,
>
> I am new to R, using decision tree model for getting segmentation rules.
> A) Using behavioural data (attributes defining customer behaviour, (
> example
> balances, number of accounts etc.)
> 1. Clustering:  Cluster behavioural data to suitable number of clusters
> 2. Decision Tree: Using rpart classification tree for generating rules for
> segmentation using cluster number(cluster id) as target variable and
> variables from behavioural data as input variables.
>
> B) Using profile data (customers  demographic data )
> 1. Clustering:  Cluster profile data to suitable number of clusters
> 2. Decision Tree: Using rpart classification tree for generating rules for
> segmentation using cluster number(cluster id) as target variable and
> variables from profile data as input variables.
>
> C) Using profile data (customers  demographic data ) and deciles created
> based on behaviour
> 1. Deciles:  Deciles customers to 10 groups based on some behavioural data
> 2. Decision Tree: Using rpart classification for generating rules for
> segmentation using Deciles  as target variable and variables from profile
> data as input variables.
>
> In first two cases A and B decision tree model using rpart finish the
> execution in a minute or two, But in third case (C) it continues to run for
> infinite amount of time( monitored and running even after 14 hours).
>  fit <- rpart(decile ~., method="class",    data=dtm_ip)
> Is there anything wrong with my approach?
>
> Thanks for the help in advance.
> -Ajit
>
>
> --
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>
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