included the code I used at the top of the document. Below
that is the version of R used and some of the results I obtained.
Many thanks!
Amber
On Wed, 4 Jun 2014 09:12:15 +0200 (CEST)
Torsten Hothorn wrote:
On Tue, 3 Jun 2014, Amber Dawn Nolder wrote:
I apologize for my lack of knowledge
Hi all,
I've been using the randomForest package and I'm trying to make the switch
over to party. My problem is that I have an extremely unbalanced outcome
(only 1% of the data has a positive outcome) which makes resampling methods
necessary.
randomForest has a very useful argument that is samp
Axel,
you need a model for such type of analyses and coin is completely
model-free.
Torsten
On Mon, 23 Sep 2013, Axel Urbiz wrote:
Dear List,
I'm interested in performing a permutation test on the interaction between a
binary treatment
indicator and a covariate (either continuous or categ
I would like to build a forest of regression trees to see how well some
covariates predict a response variable and to examine the importance of
the
covariates. I have a small number of covariates (8) and large number of
records (27368). The response and all of the covariates are continuous
vari
-- Forwarded message --
Date: Wed, 5 Oct 2011 21:09:41 +
From: Chris
To: r-h...@stat.math.ethz.ch
Subject: Re: [R] Party extract BinaryTree from cforest?
I found an internal workaround to this to support printing and plot type
simple,
tt<-party:::prettytree(cf at ensembl
New package `partykit': A Toolkit for Recursive Partytioning
The purpose of the package is to provide a toolkit with infrastructure for
representing, summarizing, and visualizing tree-structured regression and
classification models. Thus, the focus is not on _inferring_ such a
tree structure fro
fixed @ R-forge. New version should appear on CRAN soon.
Thanks for the report!
Torsten
-- Forwarded message --
Date: Sat, 3 Sep 2011 23:56:35 +0200
From: Ulrich Halekoh
To: "r-help@r-project.org"
Subject: [R] glht (multcomp): NA's for confidence intervals using
univaria
-- Forwarded message --
Date: Mon, 18 Jul 2011 10:17:00 -0700 (PDT)
From: KHOFF
To: r-help@r-project.org
Subject: [R] cforest - keep.forest = false option?
Hi,
I'm very new to R. I am most interested in the variable importance
measures
that result from randomForest, but many
dition on and thats way to much. You can
reduce the number of conditioning variables by increasing the `threshold'
parameter to something like .8
Best,
Torsten
there is a factor with (too) many levels in your data frame `rawinput'.
summary(rawinput)
will tell you which one.
T
Hello everyone,
I use the following command lines to get important variable from training
dataset.
data.controls <- cforest_unbiased(ntree=500, mtry=3)
data.cforest <- cforest(V1~.,data=rawinput,controls=data.controls)
data.cforest.varimp <- varimp(data.cforest, conditional = TRUE)
I got er
On Wed, 20 Apr 2011, Ravi Varadhan wrote:
If you had told us what the error message was, my job would have been easier.
But, at least you provied the code, so it was not hard for me to see where the
problem was. There is a problem with the strategy used by `qmvnorm' to locate
the initial i
On Thu, 17 Feb 2011, Andrew Ziem wrote:
After ctree builds a tree, how would I determine the direction missing values
follow by examining the BinaryTree-class object? For instance in the example
below Bare.nuclei has 16 missing values and is used for the first split, but
the missing values
Dear Ken,
it works for me on Linux. However, the print() commands around plot() are
not necessary.
Torsten
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On Fri, 18 Dec 2009, Achim Zeileis wrote:
On Fri, 18 Dec 2009, chrischizinski wrote:
Just in case anyone ever has similar issues, it appears that 'glht' does
not work without an intercept.
That is not precise enough to be useful. I've had a look again and appears to
be the case that mcp()
On Sun, 22 Nov 2009, Ravi Varadhan wrote:
Hi Torsten,
Hi Ravi,
It would be useful to "warn" the users that the multivariate normal probability
calculated by "pmvnorm" using the GenzBretz algorithm is "random", i.e.
the result can vary between repeated executions of the function.
only i
;. An easy
approach would be to simply write a script to generate n.rand numbers,
records the .Random.seed and proceeds in that manner- inelegant, but
effective. My question here is "Is there a better way?"
(mvtnorm part directed to Torsten Hothorn)
To further clarify, it seems there
Date: Fri, 5 Jun 2009 16:09:42 -0700 (PDT)
From: Thomas Lumley
To: dylan.beaude...@gmail.com
Cc: "'r-h...@stat.math.ethz.ch'"
Subject: Re: [R] OT: a weighted rank-based, non-paired test statistic ?
On Fri, 5 Jun 2009, Dylan Beaudette wrote:
Is anyone aware of a rank-based, non-paired test suc
u is not equal to 0
Thanks, Duncan.
Torsten
I've cc'd Torsten Hothorn, the maintainer of coin.
Duncan Murdoch
Thank you,
Matthieu
Matthieu Dubois
Post-doctoral fellow
Psychology and NeuroCognition Lab (CNRS UMR 5105)
Université Pierre Mendès-France
BP47 --- 38040 Grenoble
Hi Robb,
the gamboost() function in package `mboost' may help. The details
are described in
@article{Kneib+Hothorn+Tutz:2009,
author = {Thomas Kneib and Torsten Hothorn and Gerhard Tutz},
title = {Variable Selection and Model Choice in Geoadditive Regression
Models},
jo
Hello
Is there exists a package for multivariate random forest, namely for
multivariate response data ? It seems to be impossible with the
"randomForest" function and I did not find any information about this
in the help pages ...
party:::cforest can do, here is an example:
y <- matrix(rnor
g case weights. I believe you
> can avoid that by setting the control params to their minimum and relying on
> pruning.
>
> BTW, it is inaccurate to call these trees 'non-pruned' -- the default
> setting of cp is still (potentially) doing quite a lot of pruning.
>
Dear useRs,
The December 2007 issue of `R News' is now available on CRAN under the
Documentation/Newsletter link.
Torsten
(on behalf of the R News Editorial Board)
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Dear useRs,
The October 2007 issue of R News is now available on CRAN under the
Documentation/Newsletter link.
Torsten
(on behalf of the R News Editorial Board)
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