[R] logistic regression tree

[Frank Harrell]

It would be good to tell us of the frequency of observations in each 
category of Y, and the number of continuous X's.  Recursive 
partitioning will require perhaps 50,000 observations in the less 
frequent Y category for its structure and predicted values to 
validate, depending on X and the signal:noise ratio.  Hence the use of 
combinations of trees nowadays as opposed to single trees.  Or 
logistic regression.

Frank

Frank E Harrell Jr   Professor and Chairman        School of Medicine
                      Department of Biostatistics   Vanderbilt University

On Fri, 20 Aug 2010, Kay Cichini wrote:

>
> hello gavin & achim,
>
> thanks for responding.
>
> by logistic regression tree i meant a regression tree for a binary response
> variable.
> but as you say i could also use a classification tree - in my case with only
> two outcomes.
>
> i'm not aware if there are substantial differences to expect for the two
> approaches (logistic regression tree vs. classification tree with two
> outcomes).
>
> as i'm new to trees / boosting / etc. i also might be advised to use the
> more comprehensible method / a function which argumentation is understood
> without having to climb a steep learning ledder, respectively. at the moment
> i don't know which this would be.
>
> regarding the meaning of absences at stands: as these species are frequent
> in the area and hence there is no limitation by propagules i guess absence
> is really due to unfavourable conditions.
>
> thanks a lot,
> kay
>
>
>
> -----
> ------------------------
> Kay Cichini
> Postgraduate student
> Institute of Botany
> Univ. of Innsbruck
> ------------------------
>
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