Displaying 20 results from an estimated 2000 matches similar to: "about randomForest"
2003 Apr 12
5
rpart vs. randomForest
Greetings. I'm trying to determine whether to use rpart or randomForest
for a classification tree. Has anybody tested efficacy formally? I've
run both and the confusion matrix for rf beats rpart. I've looking at
the rf help page and am unable to figure out how to extract the tree.
But more than that I'm looking for a more comprehensive user's guide
for randomForest including
2010 Jul 14
1
randomForest outlier return NA
Dear R-users,
I have a problem with randomForest{outlier}.
After running the following code ( that produces a silly data set and builds
a model with randomForest ):
#######################
library(randomForest)
set.seed(0)
## build data set
X <- rbind( matrix( runif(n=400,min=-1,max=1), ncol = 10 ) ,
rep(1,times= 10 ) )
Y <- matrix( nrow = nrow(X), ncol = 1)
for( i in (1:nrow(X))){
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
2012 Feb 01
1
randomForest: proximity for new objects using an existing rf
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2010 Oct 21
1
RandomForest Proximity Matrix
Greetings R Users!
I am posting to inquire about the proximity matrix in the randomForest
R-package. I am having difficulty pushing very large data through the
algorithm and it appears to hang on the building of the prox matrix. I have
read on Dr. Breiman's website that in the original code a choice can be made
between using an N x N matrix OR to increase the ability to compute large
2012 Mar 23
1
Memory limits for MDSplot in randomForest package
Hello,
I am struggling to produce an MDS plot using the randomForest package
with a moderately large data set. My data set has one categorical
response variables, 7 predictor variables and just under 19000
observations. That means my proximity matrix is approximately 133000
by 133000 which is quite large. To train a random forest on this large
a dataset I have to use my institutions high
2011 Oct 05
3
help with regexp
Dear list memebers,
I am stuck with using regular expressions.
Imagine I have a vector of character strings like:
test <- c('filename_1_def.pdf', 'filename_2_abc.pdf')
How could I use regexpressions to extract only the 'def'/'abc' parts of these strings?
Some try from my side yielded no results:
testresults <-
2004 Oct 13
1
random forest -optimising mtry
Dear R-helpers,
I'm working on mass spectra in randomForest/R, and following the
recommendations for the case of noisy variables, I don't want to use the
default mtry (sqrt of nvariables), but I'm not sure up to which
proportion mtry/nvariables it makes sense to increase mtry without
"overtuning" RF.
Let me tell my example: I have 106 spectra belonging to 4 classes, the
2010 May 04
1
randomforests - how to classify
Hi,
I'm experimenting with random forests and want to perform a binary
classification task.
I've tried some of the sample codes in the help files and things run, but I
get a message to the effect 'you don't have very many unique values in the
target - are you sure you want to do regression?' (sorry, don't know exact
message but r is busy now so can't check).
In
2011 Jan 20
1
randomForest: too many elements specified?
I getting "Error in matrix(0, n, n) : too many elements specified"
while building randomForest model, which looks like memory allocation
error.
Software versions are: randomForest 4.5-25, R version 2.7.1
Dataset is big (~90K rows, ~200 columns), but this is on a big machine (
~120G RAM)
and I call randomForest like this: randomForest(x,y)
i.e. in supervised mode and not requesting
2006 Mar 08
1
Unsupervised RandomForest
Dear all,
I am trying to calculate the proximity matrix for a data set with 16 variables
and 6804 observations using random forests. I have a Pentium 4, 3.00GHz
processor with 1 GB of RAM. When I use the command
randomForest(data.scale,proximity=T)
I get the warning message
Error: cannot allocate vector of size 361675 kb
Is this because I have reached the limit of what my computer is
2006 Jan 03
1
randomForest - classifier switch
Hi
I am trying to use randomForest for classification. I am using this
code:
> set.seed(71)
> rf.model <- randomForest(similarity ~ ., data=set1[1:100,],
importance=TRUE, proximity=TRUE)
Warning message:
The response has five or fewer unique values. Are you sure you want to
do regression? in: randomForest.default(m, y, ...)
> rf.model
Call:
randomForest(x = similarity ~ .,
2003 Apr 21
2
randomForest crash?
I am attempting to use randomForests to look for interesting genes in
microarray data with 216genes, 2 classes and 52 samples. My data.frame
is 52x217 with the last column, V217 being the class(1 or 2).
When I try
lung.rf <- randomForest(V217 ~ ., data=tlSA216cda, importance=
TRUE, proximity = TRUE)
the GUI crashes.
I am running R-1.6.2 under windo$e98, and most
2002 Apr 02
2
random forests for R
Hi all,
There is now a package available on CRAN that provides an R interface to Leo
Breiman's random forest classifier.
Basically, random forest does the following:
1. Select ntree, the number of trees to grow, and mtry, a number no larger
than number of variables.
2. For i = 1 to ntree:
3. Draw a bootstrap sample from the data. Call those not in the bootstrap
sample the
2002 Apr 02
2
random forests for R
Hi all,
There is now a package available on CRAN that provides an R interface to Leo
Breiman's random forest classifier.
Basically, random forest does the following:
1. Select ntree, the number of trees to grow, and mtry, a number no larger
than number of variables.
2. For i = 1 to ntree:
3. Draw a bootstrap sample from the data. Call those not in the bootstrap
sample the
2013 Mar 29
1
Create values based on a table of conditions
Hi R help forum,
I have a simple data frame of four columns - one of numbers (really a
categorical variable), one of dates and one
of data. I have over 500,000 data points to work with, spread over 40
files, each named after a different animal.
These are contact data recorded by proximity loggers over two years
between the animals of the file name and
collars being worn by other animals. The
2007 Feb 01
3
SEXP i/o, .Call(), and garbage collection.
Apologies for any obtuseness in the following. We have been working
on Version 2.0 of the randomSurvivalForest CRAN package and we're
encountering a perplexing 'memory not mapped' segfault that we believe
is "influenced" by GC.
We essentially have two R functions, rsf.default(..), and
predict.rsf(..) and two corresponding entry points, rsfGrow(...), and
rsfPredict(...),
2023 May 09
1
RandomForest tuning the parameters
Hi Sacha,
On second thought, perhaps this is more the direction that you want ...
X2 = cbind(X_train,y_train)
colnames(X2)[3] = "y"
regr2<-randomForest(y~x1+x2, data=X2,maxnodes=10, ntree=10)
regr
regr2
#Make prediction
predictions= predict(regr, X_test)
predictions2= predict(regr2, X_test)
HTH,
Eric
On Tue, May 9, 2023 at 6:40?AM Eric Berger <ericjberger at gmail.com>
2010 Dec 27
1
Queue Member relationship and AstDB
I need clarification on couple of issues of Realtime Queue.
It seems that when Agents(Memebers) are added using AddQueueMember, Asterisk
puts this Queue-Member relationship information into AstDB, So that on
asterisk restart this can be preserved.
My question is, why does asterisk not store call information for Queue
(holdtime, talktime, W, C, A, SL%) in AstDB, So that it can also be retained
2005 Aug 11
1
username map file to link Domain groups to user
Morning to all,
Question: is it possible to use the username map file to link a domain
group - as supplied by wbinfo -u with a sigle local (/etc/passwd) user,
so that only domain memebers of that group can access a particular
share, but from the shares point of view it is accessed by the same
user?
Cheers,
Boris
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