[R] Good Decision Trees with Product Purchased Data?

[Bert Gunter]

Post on a statistics or data mining discussion site (e.g.
stats.stackexchange.com). There are tons of different algorithms for
fitting decision trees, and you are more likely to get an informative
discussion on their relative strengths and weaknesses there than here.
This is really NOT an R question.

-- Bert

Also, see below for a comment.

On Tue, Jun 5, 2012 at 1:42 PM, VikR <vikr at mindspring.com> wrote:
> A client has inquired about producing a decision tree from data which could
> include:
>
> - ID of brand purchased
> - Importance ratings (1-10 scale) for a number of relevant attributes
> (price, strength, recommended by a friend, etc.)  In other words, a rating
> of how important each attribute is in the decision as to which brand to
> purchase.
>
> I've just run a test decision tree using the closest thing to a similar data
> set, that I have at hand .  But only one attribute was selected for
> plotting.  I used the "Tree" package for this test.
>
> Question:
> - Does one usually get good decision trees using data of this kind?
???
Define: "one" (who?)
Define: "usually"
Define: "good"
Define: "data of this kind"

>
> Thanks very much in advance to all for any info.
>
> --
> View this message in context: http://r.789695.n4.nabble.com/Good-Decision-Trees-with-Product-Purchased-Data-tp4632438.html
> Sent from the R help mailing list archive at Nabble.com.
>
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-- 

Bert Gunter
Genentech Nonclinical Biostatistics

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