Displaying 20 results from an estimated 200 matches similar to: "Party package: varimp(..., conditional=TRUE) error: term 1 would require 9e+12 columns"
2011 Oct 17
0
Party package: varimp(..., conditional=TRUE) error: term 1 would require 9e+12 columns (fwd)
>
> 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
> variables.
>
> A cursory examination of the covariates does not
2012 Apr 29
1
CForest Error Logical Subscript Too Long
Hi,
This is my code (my data is attached):
library(languageR)
library(rms)
library(party)
OLDDATA <- read.csv("/Users/Abigail/Documents/OldData250412.csv")
OLDDATA$YD <- factor(OLDDATA$YD, label=c("Yes", "No"))?
OLDDATA$ND <- factor(OLDDATA$ND, label=c("Yes", "No"))?
attach(OLDDATA)
defaults <- cbind(YD, ND)
set.seed(47)
data.controls
2013 Feb 14
1
party::cforest - predict?
What is the function call interface for predict in the package party for
cforest? I am looking at the documentation (the vignette) and ?cforest and
from the examples I see that one can call the function predict on a cforest
classifier. The method predict seems to be a method of the class
RandomForest objects of which are returned by cforest.
---------------------------
> cf.model =
2012 Dec 11
2
VarimpAUC in Party Package
Greetings! I'm trying to use function varimpAUC in the party package (party_1.0-3 released September 26th of this year). Unfortunately, I get the following error message:
> data.cforest.varimp <- varimpAUC(data.cforest, conditional = TRUE)
Error: could not find function "varimpAUC"
Was this function NOT included in the Windows binary I downloaded and installed? Could someone
2008 Sep 25
0
varimp in party (or randomForest)
Hi,
There is an excellent article at http://www.biomedcentral.com/1471-2105/9/307 by Stroble, et al. describing variable importance in random forests. Does anyone have any suggestions (besides imputation or removal of cases) for how to deal with data that *have* missing data for predictor variables?
Below is an excerpt of some code referenced in the article. I have commented out one line and
2009 May 16
5
bagged importance estimates in earth problem
I was trying to produced bagged importance estimates of attributes in earth using the caret package with the following commands:
fit2 <- bagEarth(loyalty ~ ., data=model1, B = 10)
bagImpGCV <- varImp(fit2,value="gcv")
My bootstrap estimates are produced however the second command "varImp" produces the following error:
Error in UseMethod("varImp") : no
2011 Mar 07
2
use "caret" to rank predictors by random forest model
Hi,
I'm using package "caret" to rank predictors using random forest model and draw predictors importance plot. I used below commands:
rf.fit<-randomForest(x,y,ntree=500,importance=TRUE)
## "x" is matrix whose columns are predictors, "y" is a binary resonse vector
## Then I got the ranked predictors by ranking
2012 Oct 11
0
Error with cForest
All --
I have been trying to work with the 'Party' package using R v2.15.1 and have cobbled together a (somewhat) functioning code from examples on the web. I need to run a series of unbiased, conditional, cForest tests on several subsets of data which I have made into a loop. The results ideally will be saved to an output file in matrix form. The two questions regarding the script in
2011 Jun 16
1
Fwd: varimp_in_party_package
>
> 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 error: "Error in
2004 Apr 05
3
Can't seem to finish a randomForest.... Just goes and goe s!
When you have fairly large data, _do not use the formula interface_, as a
couple of copies of the data would be made. Try simply:
Myforest.rf <- randomForest(Mydata[, -46], Mydata[,46],
ntrees=100, mtry=7)
[Note that you don't need to set proximity (not proximities) or importance
to FALSE, as that's the default already.]
You might also want to use
2009 Feb 06
0
party package conditional variable importance
Hello,
I'm trying to use the party package function varimp() to get
conditional variable importance measures, as I'm aware that some of my
variables are correlated. However I keep getting error messages (such
as the example below). I get similar errors with three separate
datasets that I'm using. At a guess it might be something to do with
the very large number of variables (e.g.
2004 Apr 05
2
Can't seem to finish a randomForest.... Just goes and goes!
Alternatively, if you can arrive at a sensible ordering of the levels
you can declare them ordered factors and make the computation feasible
once again.
Bill Venables.
-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch
[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Torsten Hothorn
Sent: Monday, 5 April 2004 4:27 PM
To: David L. Van Brunt, Ph.D.
Cc: R-Help
Subject:
2008 Apr 04
1
random forest varimp
Friends,
I have noticed that many publications that use RF report variable importance as
a function of mean decrease in accuracy rather than mean decrease in gini. Am I
correct that the mean decrease in accuracy is just the mean decrease in gini
divided by 100?
Thanks,
Helen Mills Poulos
Yale School of Forestry
2012 Nov 22
1
Partial dependence plot in randomForest package (all flat responses)
Hi,
I'm trying to make a partial plot with package randomForest in R. After I
perform my random forest object I type
partialPlot(data.rforest, pred.data=act2, x.var=centroid, "C")
where data.rforest is my randomforest object, act2 is the original dataset,
centroid is one of the predictor and C is one of the classes in my response
variable.
Whatever predictor or response class I
2012 Dec 06
0
Package party Error in model.matrix.default(as.formula(f), data = blocks) :allocMatrix: too many elements specified
Dear all:
I¡¯m trying to get unbiased feature importance of my data via package ¡°party¡±, which contains 1-5 integer value, and a few numeric values attributes. The class label is 1-5 integer value as well. In total I have 20 features with 1100 observations. I checked the type my data in R using class(my_data_cell), no factor has been observed. I received a commond error like others did
2013 Jan 11
0
Error with looping through a list of strings as variables
Dear R users:
I have been trying to figure out how to include string variables in a for
loop to run multiple random forests with little success. The current code
returns the following error:
Error in trafo(data = data, numeric_trafo = numeric_trafo, factor_trafo =
factor_trafo, :
data class character is not supported
In addition: Warning message:
In storage.mode(RET@predict_trafo) <-
2010 Mar 23
1
caret package, how can I deal with RFE+SVM wrong message?
Hello,
I am learning caret package, and I want to use the RFE to reduce the
feature. I want to use RFE coupled Random Forest (RFE+FR) to complete this
task. As we know, there are a number of pre-defined sets of functions, like
random Forest(rfFuncs), however,I want to tune the parameters (mtr) when
RFE, and then I write code below, but there is something wrong message, How
can I deal with it?
2010 Jun 10
2
Cforest and Random Forest memory use
Hi all,
I'm having great trouble working with the Cforest (from the party package)
and Random forest functions. Large data set seem to create very large model
objects which means I cannot work with the number of observations I need to,
despite running on a large 8GB 64-bit box. I would like the object to only
hold the trees themselves as I intend to export them out of R. Is there
anyway,
2004 Dec 06
0
errors from ads_krb5_mk_req errors and util_sock.c:send_smb
After 2 weeks of trying to configure samba as a member server in a
native AD domain, with winbind+nss+kerberose following the Samba
Collection and (Samba-3 By Exmaple) docuentation, with RedHat AS3,
samba 3.0.9, krb5 1.3.1, where 2 KDC's are Windows 2003 and one is
Windows 2000, and smb-signing has been turned off,...
when a user tries to access a share, they are prompted for a password,
and
2010 Jul 27
1
Cforest mincriterion
Hi,
Could anyone help me understand how the mincriterion threshold works in
ctree and cforest of the party package? I've seen examples which state that
to satisfy the p < 0.05 condition before splitting I should use mincriterion
= 0.95 while the documentation suggests I should use mincriterion =
qnorm(0.95) which would obviously feed the function a different value.
Thanks in advance,