Dear Eric thanks for your code,
Dear R-experts,
Here below my R code, still the same error message at the end while trying to
tune the parameters!
Any hints to make it work would be appreciated.
Best,
# Create features a
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,
Hi,
One problem you have is with the command:
regr<-randomForest(y~x1+x2, data=X_train, proximity=TRUE)
What you need is something like this:
X2 <- cbind(X,y)
regr<-randomForest(y~x1+x2, data=X2, proximity=TRUE)
HTH,
Eric
On Mon, May 8, 2023 at 11:11 PM varin sacha via R-help
wrote:
>
> Dear
Dear R-experts,
Here below a toy example with some error messages, especially at the end of the
code (Tuning the parameters). Your help to correct my R code would be highly
appreciated.
###
#libraries
library(lattice)
library(ggplot2)
library(caret)
library(
accuracies are not unexpected.
Gesendet von Mail für Windows 10
Von: Witold E Wolski
Gesendet: Samstag, 12. Januar 2019 18:56
An: r-help@r-project.org
Betreff: [R] randomForest out of bag prediction
Hello,
I am just not sure what the predict.RandomForest function is doing...
I confused.
I would expect
See inline.
On Sat, Jan 12, 2019 at 9:56 AM Witold E Wolski wrote:
> ypred_oob <- predict(diachp.rf)
AFAIK these are, indeed, the out-of-bag predictions.
> dataX <- data %>% select(-quality) # remove response.
> ypred <- predict( diachp.rf, dataX )
These are not out of bag predictions. dataX
Off topic.
But see here:
https://stats.stackexchange.com/questions/61405/random-forest-and-prediction
-- Bert
Bert Gunter
"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Sa
Hello,
I am just not sure what the predict.RandomForest function is doing...
I confused.
I would expect the predictions for these 2 function calls to predict the same:
```{r}
diachp.rf <- randomForest(quality~.,data=data,ntree=50, importance=TRUE)
ypred_oob <- predict(diachp.rf)
dataX <- data %>
I am looking at results of a random forest. In the documentation, it says
the following for categorical variables:
"For categorical predictors, the splitting point is represented by an
integer, whose binary expansion gives the identities of the categories that
goes to left or right. For example, i
I'm been experimenting with the randomForest R package (v. 4.6-12) and getting
an unexpected difference between rpart and randomForest results that may have
something to do with using x's that are factors.
The same model (see code below) is used to predict a 2-value variable called
"resp" tha
Please post in plain text, and supply a reproducible example (that
includes sample data, preferably using the dput function).
The below code obtains repeatable random number sequences in each pass
through the loop, as confirmed by the first value in each sequence.
##
a <- 0
##
## For loop to
Dear forum members,
I wrote a piece of code to test various combinations of mtry and ntree, so
that the best combination (in terms of mse) could be used. Before each
randomForest command I included a set.seed() command, so that I can keep
track of the seed number and replicate the results. Howev
667
Chlorophyll
> # End
-Original Message-
From: Liaw, Andy [mailto:andy_l...@merck.com]
Sent: 25 March 2014 02:37 AM
To: Sean Porter; r-help@r-project.org
Subject: RE: [R] randomForest warning: The response has five or fewer unique
values. Are you sure you want to do r
it a factor.
Best,
Andy Liaw
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf Of Sean Porter
Sent: Thursday, March 20, 2014 3:27 AM
To: r-help@r-project.org
Subject: [R] randomForest warning: The response has five or fewer unique
value
Hello everyone,
Im relatively new to R and new to the randomForest package and have scoured
the archives for help with no luck. I am trying to perform a regression on a
set of predictors and response variables to determine the most important
predictors. I have 100 response variables collected f
Dear Dennis and dear All,
It was probably not my best post.
I am running R on a Debian box (amd64 architecture) and that is why I
was surprised to see memory issues when dealing with a vector larger
than 1Gb. The memory is there, but probably it is not contiguous.
I will investigate into the matter
On Sun, 3 Feb 2013, Lorenzo Isella wrote:
Dear All,
For a data mining project, I am relying heavily on the RandomForest and Party
packages.
Due to the large size of the data set, I have often memory problems (in
particular with the Party package; RandomForest seems to use less memory). I
real
Neither of your questions meets the Posting Guidelines (see footer of any
email).
1) Not reproducible. [1]
2) Very operating-system specific and a FAQ. You have not indicated what your
OS is (via sessionInfo), nor what reading you have done to address memory
problems already (use a search engine
Dear All,
For a data mining project, I am relying heavily on the RandomForest and
Party packages.
Due to the large size of the data set, I have often memory problems (in
particular with the Party package; RandomForest seems to use less memory).
I really have two questions at this point
1) Pl
If you wish to remove missing values, you can use the option
na.action=na.omit.If you wish to Impute you can use rfImpute.
--- On Mon, 28/1/13, Lorenzo Isella wrote:
From: Lorenzo Isella
Subject: [R] RandomForest and Missing Values
To: r-h...@stat.math.ethz.ch
Date: Monday, 28 January, 2013
Dear All,
I would like to use a randomForest algorithm on a dataset.
The set is not particularly large/difficult to handle, but it has some
missing values (both factors and numerical values).
According to what I found
https://stat.ethz.ch/pipermail/r-help/2005-September/078880.html
https://stat.et
uld be avoided with large datasets.
Andy
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf Of John Foreman
Sent: Monday, December 03, 2012 3:43 PM
To: r-help@r-project.org
Subject: [R] How do I make R randomForest model size smaller?
I've been training randomForest models on 7 million rows of data (41
features). Here's an example call:
myModel <- randomForest(RESPONSE~., data=mydata, ntree=50, maxnodes=30)
I thought surely with only 50 trees and 30 terminal nodes that the memory
footprint of "myModel" would be small. But it's
Hi,
I appologise if this is a rudimentary question and long winded but I just
wanted to let ye know where I'm comming from. I'm new to R and I'm trying to
use the 'randomForest' package to classify and predict. The Error message
that is troubling me is:
> pr<-predict(predictors,rf1, ext=ext)
Error
Hi Jim
I am unable to access the webinar pdf on RandomForest Implementation. Can you
please send it over?
Regards
--
Gautami
This email message may contain proprietary, private and confidential
information. The information transmitted is intended only for the
Hi
I have a dataset with a few variables but two variables are very important.
One of them is say S1 and other S2. S1 is a numeric variable and S2 is a
categorical variable. Consider two cases of S1-S2 pair like S1 = 70.2, S2 =
A and S1 = 70.21, S2 = B. Assume my dataset has 20 instances of the f
Peter,
Thanks for checking on this! We're having some difficulties forecasting
sales ... randomForest is doing a great job on days and periods where there
is high variability. However, such as in this case, we do get
dates/times/departments where it simply forecasts the most frequent value
(I un
Well, if you look at your data more carefully, you will see that the
histogram of y is heavily skewed towards 1 (small values). The 91/625
quantile is still 1 (there are 192 1s). It is therefore not surprising
that RF comes up with mostly 1s (in my attempt it came up with two 2s,
but that is a bit
We have a pretty simple R forecasting problem, using randomForest. Our
script is below. We have data with about 6 columns, and 625 rows to do the
training on, and then we're trying to forecast 90 or so rows.
The x matrix has 3 years worth of sales data, starting at 6:15am. However,
for some rea
ent: Wednesday, February 01, 2012 5:39 AM
> To: r-help@r-project.org
> Subject: [R] randomForest: proximity for new objects using an
> existing rf
>
> Dear all,
>
> using an existing random forest, I would like to calculate
> the proximity
> for a new test object, i.e.
Dear all,
using an existing random forest, I would like to calculate the proximity
for a new test object, i.e. the similarity between the new object and the
old training objects which were used for building the random forest. I do
not want to build a new random forest based on both old and new obj
Here is a snippet to show what i'm trying to do.
library(randomForest)
library(ROCR)
library(caret)
data(iris)
iris <- iris[(iris$Species != "setosa"),]
fit <- randomForest(factor(Species) ~ ., data=iris, ntree=50)
train.predict <- predict(fit,iris,type="prob")[,2]
plot(performance(prediction(t
p-boun...@r-project.org
> [mailto:r-help-boun...@r-project.org] On Behalf Of Katharine Miller
> Sent: Tuesday, September 20, 2011 1:43 PM
> To: r-help@r-project.org
> Subject: [R] randomForest - NaN in %IncMSE
>
> Hi
>
> I am having a problem using varImpPlot in randomFo
Hi
I am having a problem using varImpPlot in randomForest. I get the error
message "Error in plot.window(xlim = xlim, ylim = ylim, log = "") : need
finite 'xlim' values"
When print $importance, several variables have NaN under %IncMSE. There
are no NaNs in the original data. Can someone hel
Message-
>> From: r-help-boun...@r-project.org
>> [mailto:r-help-boun...@r-project.org] On Behalf Of John Foreman
>> Sent: Wednesday, September 07, 2011 2:46 PM
>> To: r-help@r-project.org
>> Subject: [R] randomForest memory footprint
>>
>> Hello, I am att
an 10 terminal nodes per tree).
Best,
Andy
> -Original Message-
> From: r-help-boun...@r-project.org
> [mailto:r-help-boun...@r-project.org] On Behalf Of John Foreman
> Sent: Wednesday, September 07, 2011 2:46 PM
> To: r-help@r-project.org
> Subject: [R] randomForest memory foo
Hello, I am attempting to train a random forest model using the
randomForest package on 500,000 rows and 8 columns (7 predictors, 1
response). The data set is the first block of data from the UCI
Machine Learning Repo dataset "Record Linkage Comparison Patterns"
with the slight modification that I
[i]), ylim=c(30, 70))
}
par(op)
Andy
> -Original Message-
> From: r-help-boun...@r-project.org
> [mailto:r-help-boun...@r-project.org] On Behalf Of Katharine Miller
> Sent: Thursday, August 04, 2011 4:38 PM
> To: r-help@r-project.org
> Subject: [R] randomForest p
Hello,
I am running randomForest models on a number of species. I would like to be
able to automate the printing of dependence plots for the most important
variables in each model, but I am unable to figure out how to enter the
variable names into my code. I had originally thought to extract the
gt; From: r-help-boun...@r-project.org
> [mailto:r-help-boun...@r-project.org] On Behalf Of Czerminski, Ryszard
> Sent: Thursday, January 20, 2011 1:08 PM
> To: r-h...@stat.math.ethz.ch
> Subject: [R] randomForest: too many elements specified?
>
> I getting "Error in matrix
rd.czermin...@astrazeneca.com
RE: [R] randomForest: too many element specified?
Liaw, Andy
Mon, 17 Jan 2005 05:56:28 -0800
> From: luk
>
> When I run randonForest with a 169453x5 matrix, I got the
> following message.
>
> Error in matrix(0, n, n) : matrix: too many elements specified
>
&g
> > Sent: Tuesday, January 04, 2011 6:30 PM
> > To: r-help@r-project.org
> > Subject: Re: [R] randomForest speed improvements
> >
> >
> > Andy,
> >
> > Thanks for the reply. I had no idea I could combine them
> > back ... that
> >
egrading.
Andy
> -Original Message-
> From: r-help-boun...@r-project.org
> [mailto:r-help-boun...@r-project.org] On Behalf Of apresley
> Sent: Tuesday, January 04, 2011 6:30 PM
> To: r-help@r-project.org
> Subject: Re: [R] randomForest speed improvements
>
>
> Andy,
&
Andy,
Thanks for the reply. I had no idea I could combine them back ... that
actually will work pretty well. We can have several "worker threads" load
up the RF's on different machines and/or cores, and then re-assemble them.
RMPI might be an option down the road, but would be a bit of overhea
ng only certain quantiles. The current RF code
doesn't do this.
Andy
> -Original Message-
> From: r-help-boun...@r-project.org
> [mailto:r-help-boun...@r-project.org] On Behalf Of apresley
> Sent: Monday, January 03, 2011 6:28 PM
> To: r-help@r-project.org
> Subject: R
I haven't tried changing the mtry or ntree at all ... though I suppose with
only 6 variables, and tens-of-thousands of rows, we can probably do less
than 500 tree's (the default?).
Although tossing the forest does speed things up a bit, seems to be about 15
- 20% faster in some cases, I need to k
ord... imbue it."
- Jubal Early, Firefly
r-help-boun...@r-project.org wrote on 01/03/2011 02:59:29 PM:
> [image removed]
>
> [R] randomForest speed improvements
>
> apresley
>
> to:
>
> r-help
>
> 01/03/2011 03:03 PM
>
> Sent by:
>
> r-help
Hi there,
We're trying to use randomForest to do some predictions. The test-harness
for our code is pretty straightforward:
library ('randomForest');
data202 <- read.csv ("random.csv", header=TRUE);
x<- data202[1:5,1:6];
y<- data202[1:5,8];
y<- y[,drop=TRUE];
x2 <- data202[
Since we do not have the data, it is hard for us to reproduce and debug.
Uwe Ligges
On 21.12.2010 23:48, Dennis wrote:
Just curious if anyone else has got this error before, and if so,
would know what I could do (if anything) to get past it:
mtry<- tuneRF(training, trainingdata$class, ntre
Just curious if anyone else has got this error before, and if so,
would know what I could do (if anything) to get past it:
> mtry <- tuneRF(training, trainingdata$class, ntreeTry = 500, stepFactor = 2,
> improve = 0.05, trace = TRUE, plot = TRUE, doBest = FALSE)
mtry = 13 OOB error = 0.62%
Searc
t; To: r-help@r-project.org
> Subject: [R] randomForest: help with combine() function
>
> I've built two RF objects (RF1 and RF2) and have tried to combine
> them, but I get the following error:
>
> Error in rf$votes + ifelse(is.na(rflist[[i]]$votes), 0,
> rflist[[i]]
I've built two RF objects (RF1 and RF2) and have tried to combine
them, but I get the following error:
Error in rf$votes + ifelse(is.na(rflist[[i]]$votes), 0, rflist[[i]]$votes) :
non-conformable arrays
In addition: Warning message:
In rf$oob.times + rflist[[i]]$oob.times :
longer object lengt
-
>> From: r-help-boun...@r-project.org
>> [mailto:r-help-boun...@r-project.org] On Behalf Of Dennis Duro
>> Sent: Tuesday, December 07, 2010 11:46 AM
>> To: r-help@r-project.org
>> Subject: [R] randomForest: How to append ID column along with
>> prediction
..@r-project.org
> [mailto:r-help-boun...@r-project.org] On Behalf Of Dennis Duro
> Sent: Tuesday, December 07, 2010 11:46 AM
> To: r-help@r-project.org
> Subject: [R] randomForest: How to append ID column along with
> predictions
>
> Hi all,
>
> When running a prediction
Hi all,
When running a prediction using RF on another data, I get two columns
returned: row number(?) and predicted class. Is there a way of
appending the unique row value from an ID column in the dataframe to
the predictions instead of the row number? I'm assuming that the
returned results follow
Hi all,
When running a prediction using RF on another data, I get two columns
returned: row number(?) and predicted class. Is there a way of
appending the unique row value from an ID column in the dataframe to
the predictions instead of the row number? I'm assuming that the
returned results follow
the image in blocks and use
predict.randomForest directly.
Benjamin
-Original Message-
From: Liaw, Andy [mailto:andy_l...@merck.com]
Sent: November 18, 2010 8:39 AM
To: Deschamps, Benjamin; r-help@r-project.org
Subject: RE: [R] randomForest parameters for image classification
1. Memory
data you want to predict, not the other way around.
Andy
> -Original Message-
> From: Deschamps, Benjamin [mailto:benjamin.descha...@agr.gc.ca]
> Sent: Tuesday, November 16, 2010 11:16 AM
> To: r-help@r-project.org
> Cc: Liaw, Andy
> Subject: RE: [R] randomForest pa
ks, Benjamin
-Original Message-
From: Liaw, Andy [mailto:andy_l...@merck.com]
Sent: November 11, 2010 7:02 AM
To: Deschamps, Benjamin; r-help@r-project.org
Subject: RE: [R] randomForest parameters for image classification
Please show us the code you used to run randomForest, the output, as
well as wha
You can try ctree in package party, but anyway: what is the deeper
sense in a binary split for a variable with more than 32 levels?
Regards, Sven
2010/11/10 Erik Iverson :
> Well, the error message seems relatively straightforward.
>
> When you run str(x) (you did not provide the data)
>
> you sh
p-boun...@r-project.org
> [mailto:r-help-boun...@r-project.org] On Behalf Of Deschamps, Benjamin
> Sent: Tuesday, November 09, 2010 10:52 AM
> To: r-help@r-project.org
> Subject: [R] randomForest parameters for image classification
>
> I am implementing an image classifica
Well, the error message seems relatively straightforward.
When you run str(x) (you did not provide the data)
you should see 1 or more components are factors that have more than 32
levels. Apparently you can't include those predictors in a call
to randomForest.
You might find the following line
try to transform the attributes that have more than 32 levels into
dummy binary variables.
2010/11/10 Mai Dang :
> I received this error
> Error in randomForest.default(m, y, ...) :
> Can not handle categorical predictors with more than 32 categories.
>
> using below code
>
> library(randomForest)
I received this error
Error in randomForest.default(m, y, ...) :
Can not handle categorical predictors with more than 32 categories.
using below code
library(randomForest)
library(MASS)
memory.limit(size=12999)
x <- read.csv("D:/train_store_title_view.csv", header=TRUE)
x <- na.omit(x)
set.seed(1
I am implementing an image classification algorithm using the
randomForest package. The training data consists of 31000+ training
cases over 26 variables, plus one factor predictor variable (the
training class). The main issue I am encountering is very low overall
classification accuracy (a lot of
From: Michael Lindgren
>
> 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
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 ch
Thanks for the elaborate detailing. I see sense now.
Regards
Vijayan Padmanabhan
"What is expressed without proof can be denied without proof" - Euclide.
"Liaw, Andy"
09/24/2010 04:31 PM
To
"Vijayan Padmanabhan" , "r-help"
cc
Subject
RE: [R] r
help-boun...@r-project.org] On Behalf Of Vijayan Padmanabhan
> Sent: Wednesday, September 22, 2010 11:47 PM
> To: r-help
> Subject: [R] randomForest - PartialPlot - reg
>
>
> Dear R Group
> I am not sure if this is the right forum to raise this query,
> but i would
> rather giv
Dear R Group
I am not sure if this is the right forum to raise this query, but i would
rather give it a try and aim for reaching the right person who might be a
part of this group who can help.
I have a query on interpretation of PartialPlot in package randomForest.
In my earlier queries in thi
> From: Vijayan Padmanabhan
>
> Dear R Group
> I had an observation that in some cases, when I use the
> randomForest model
> to create partialPlot in R using the package "randomForest"
> the y-axis displays values that are more than -1!
> It is a classification problem that i was trying to addr
Dear R Group
I had an observation that in some cases, when I use the randomForest model
to create partialPlot in R using the package "randomForest"
the y-axis displays values that are more than -1!
It is a classification problem that i was trying to address.
Any insights as to how the y axis can
.org [mailto:r-help-boun...@r-project.org]
> On Behalf Of Pau Carrio Gaspar
> Sent: Wednesday, July 14, 2010 6:36 AM
> To: r-help@r-project.org
> Subject: [R] randomForest outlier return NA
>
> Dear R-users,
>
> I have a problem with randomForest{outlier}.
> Afte
anks for reporting.
Best,
Andy
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org]
On Behalf Of Pau Carrio Gaspar
Sent: Wednesday, July 14, 2010 6:36 AM
To: r-help@r-project.org
Subject: [R] randomForest outlier return NA
Dear R-users,
I have a problem
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 =
>> Would you please confirm that it is a bootstrap sample with
>> replacement?
Someone should note that the definition of a bootstrap sample is a
sample with replacement (usually of size n).
I've read quite a few papers where they claim to be using the
bootstrap. Upon further review (sometimes to
See the "replace" argument in ?randomForest.
Andy
> -Original Message-
> From: r-help-boun...@r-project.org
> [mailto:r-help-boun...@r-project.org] On Behalf Of Dimitri
> Liakhovitski
> Sent: Friday, May 07, 2010 12:21 PM
> To: r-help
> Subject:
Hello!
I know that as trees are constructed, the root node contains a
bootstrap sample of data of the same size as original the data set.
Would you please confirm that it is a bootstrap sample with replacement?
I think it is - just wanted to make sure.
Thank you very much!
--
Dimitri Liakhovitsk
>> Andy, I'll explain why I am asking. I probably should have
>> done it in the beginning:
>> I am asking not in order to figure out how to do it. I am
>> asking in order to figure something that' was done around
>> November 01, 2008.
>> Back then, a piece of code was run where from the object of
>
From: Dimitri Liakhovitski
> >> Andy, I'll explain why I am asking. I probably should have
> done it in
> >> the beginning:
> >> I am asking not in order to figure out how to do it. I am
> asking in
> >> order to figure something that' was done around November 01, 2008.
> >> Back then, a piece
Thank you very much, Andy.
I did turn off HTML - hope it'll solve the problem!
> Andy, but it is the FIRST column in $importance (not the SECOND) that is
> labeled "%IncMSE". The second column is labeled "IncNodePurity". So, I
> am confused - which one is the mean decrease in accuracy?
> Or, maybe
> From: Dimitri Liakhovitski
> Thank you very much, Andy.
> I did turn off HTML - hope it'll solve the problem!
Indeed it does!
[...]
> > [AL]: As I said, you are recommended to use importance() to extract
> > variable importance. The recommendation is for avoiding confusions
> > like yours
Not that I want to pick on you, but can you turn off the html format in
your messages? The mailing list balk at such format, and I can't reply
in plain text with the right formatting of previous messages (had to
manually remove the tabbed indents that Outlook added when changed to
plain text).
Se
Andy, thank you - and sorry for being a bit slow (see my questions below):
On Thu, May 6, 2010 at 8:37 AM, Liaw, Andy wrote:
> See reply inline below.
>
> Andy
>
> From: Dimitri Liakhovitski
> >
> > I have a question about predictor importances in randomForest.
> >
> > Once I've run randomForest
See reply inline below.
Andy
From: Dimitri Liakhovitski
>
> I have a question about predictor importances in randomForest.
>
> Once I've run randomForest and got my object, I get their importances:
> rfresult$importance
> I also get the "standard errors" of the permutation-based importance
> m
I have a question about predictor importances in randomForest.
Once I've run randomForest and got my object, I get their importances:
rfresult$importance
I also get the "standard errors" of the permutation-based importance
measure: rfresult$importanceSD
I have 2 questions:
1. Because I am dealin
HI, Andy,
ON the RandomForest diagnostics plot, three lines were drawn.
ON the help document of plot.randomForest, only the error rate and MSE are
described. I dont know which line is which?
Can you help me with that?
Thanks so much!
--
Sincerely,
Changbin
--
[[alternative HTML ver
On 25.04.2010 16:27, Rolf Edberg wrote:
Hi
I am new to R, randomForest and I have read about how to use it in your old
mails. I have also run the predictions examples from CRAN. But I still don't
understand how to use it right.
The thing that I don't understand is how to run
Hi
I am new to R, randomForest and I have read about how to use it in your old
mails. I have also run the predictions examples from CRAN. But I still don't
understand how to use it right.
The thing that I don't understand is how to run the result from the
randomForest on one
Hi,
On Thu, Apr 8, 2010 at 1:18 PM, JMark wrote:
>
> I'm trying to do:
> randomForest(f, data = moths.train)
>
> But I get this error:
> Error in randomForest.default(m, y, ...) :
> Need at least two classes to do classification.
>
> When I look at the data for this, I realize there are no posit
I'm trying to do:
randomForest(f, data = moths.train)
But I get this error:
Error in randomForest.default(m, y, ...) :
Need at least two classes to do classification.
When I look at the data for this, I realize there are no positive cases of
this item:
[1] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
.@r-project.org] On Behalf Of Epic John
> Sent: Friday, January 15, 2010 4:50 PM
> To: r-help@r-project.org
> Subject: [R] randomForest maxnodes
>
> Has anyone sucessfully used the maxnodes feature in
> randomForest? I tried
> setting it, but when it is non-NULL I always get
Has anyone sucessfully used the maxnodes feature in randomForest? I tried
setting it, but when it is non-NULL I always get back a forest in which all
trees have size 1. I am using a continuous response (regression). Any help
would be appreciated.
Thanks.
[[alternative HTML version deleted]
.
ncs
- Original Message
From: "Liaw, Andy"
To: NCS ; r-help@r-project.org
Sent: Mon, December 7, 2009 5:46:24 AM
Subject: RE: [R] RandomForest - getTree status code
Is that the entire tree? If so there's a problem. The node status is
defined as follows in rf.h of
---
> From: r-help-boun...@r-project.org
> [mailto:r-help-boun...@r-project.org] On Behalf Of NCS
> Sent: Friday, December 04, 2009 4:53 PM
> To: r-help@r-project.org
> Subject: [R] RandomForest - getTree status code
>
>
> What does a status value of -3 mean when I do
What does a status value of -3 mean when I do a regression with RF and use the
getTree function?
left daughter right daughter split var split point status prediction
12 311 4.721000e+03 -3 15.8489576
24 5 5 6.500
The NEWS of the randomForest R library mention that version 4.5-13
fixed a bug in predict.randomForest() when newdata is a matrix with no
rownames.
Can anyone explain what were the consequences of this bug in the predictions?
I think the bug was fixed with the new line
if (is.null(rn)) rn <- kee
The NEWS of the randomForest R library mention that version 4.5-13 fixed a
bug in predict.randomForest() when newdata is a matrix with no rownames.
I think it corresponds to the difference in files
predict.randomForest.R
which is the new line
if (is.null(rn)) rn <- keep
As I've been using version
Thanks for the feedback. In the meantime, is there any other way to utilize
the model outside of R, even if it is a little more complicated?
- Original Message
From: Graham Williams
To: NCS
Cc: r-help@r-project.org
Sent: Tue, November 3, 2009 9:53:10 PM
Subject: Re: [R
2009/11/4 NCS :
> I cannot seem to write a randomforest model in PMML - either through calling
> PMML(model) or through Rattle. It appears that it is not yet supported.
> Randomsurvivalforest is, but not randomforest. Any ideas on possible
> workarounds for this?
>
> Thanks
> ncs
It is not yet i
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