More than "not at all", I'd say: Decidedly ambiguous. The tree topologies
(though not necessarily the predictions) can change radically with minor
alterations to the data.
Bert Gunter
Biometrics Research RY 70-38
Merck & Company
P.O. Box 2000
Rahway, NJ 07065-0900
Phone: (732) 594-7765
mailto: bert_gunter@merck.com
"The business of the statistician is to catalyze the scientific learning
process." -- George E.P. Box
-----Original Message-----
From: Prof Brian D Ripley [mailto:ripley@stats.ox.ac.uk]
Sent: Wednesday, April 04, 2001 1:48 AM
To: Wing, Michael
Cc: s-news@wubios.wustl.edu
Subject: Re: [S] Regression Trees- Independent Variable Collinearity
On Tue, 3 Apr 2001, Wing, Michael wrote:
> Hi all,
>
> To what extent are regression tree (with a single continuous dependent
> variable) results robust in regards to collinearity or correlation between
> independent variables? I'm interested in this issue when both continuous
> and factor variables are included in the independent variables and also
when
> only continuous independent variables are used.
Not at all. Tree-based methods are not robust to many things, which is
why methods such as bagging and boosting have arisen. They were designed
to find fairly complex but clear-cut relationships.
--
Brian D. Ripley, ripley@stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272860 (secr)
Oxford OX1 3TG, UK Fax: +44 1865 272595
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