Displaying 20 results from an estimated 30000 matches similar to: "random Forests"
2010 Apr 09
1
Question on implementing Random Forests scoring
So I've been working with Random Forests ( R library is randomForest) and I
curious if Random Forests could be applied to classifying on a real time
basis. For instance lets say I've scored fraud from a group of
transactions. If I want to score any new incoming transactions for fraud
could Random Forests be used in that context. Linear Regression is nice in
that it is very easy to
2007 Aug 24
2
Variable Importance - Random Forest
Hello,
I am trying to explore the use of random forests for classification and
am certain about the interpretation of the importance measurements.
When having the option "importance = T" in the randomForest call, the
resulting 'importance' element matrix has four columns with the
following headings:
0 - mean raw importance score of variable x for class 0 (where
2009 Apr 10
1
Random Forests: Question about R^2
Dear Random Forests gurus,
I have a question about R^2 provided by randomForest (for regression).
I don't succeed in finding this information.
In the help file for randomForest under "Value" it says:
rsq: (regression only) - "pseudo R-squared'': 1 - mse / Var(y).
Could someone please explain in somewhat more detail how exactly R^2
is calculated?
Is "mse"
2008 Mar 09
1
sampsize in Random Forests
Hi all,
I have a dataset where each point is assigned to a class A, B, C, or
D. Each point is also assigned to a study site. Each study site is
coded with a number ranging between 1-100. This information is stored
in the vector studySites.
I want to run randomForests using stratified sampling, so I chose the option
strata = factor(studySites)
But I am not sure how to control the number of
2018 Jan 20
2
Random Forests
Gracias Carlos y Javier, ntrees es el nº de árboles y treesize sus
respectivos tamaños (nº de nodos)
ntree: Number of trees to grow. This should not be set to too small ......
treesize: Size of trees (number of nodes) in and ensemble.
Puse 1000 árboles (ntree=1000), si, pero la función treesize te da el
nº de nodos:
treesize(RFfit, terminal=TRUE) me da un vector de 1000 elementos (uno
2012 Dec 03
2
Different results from random.Forest with test option and using predict function
Hello R Gurus,
I am perplexed by the different results I obtained when I ran code like
this:
set.seed(100)
test1<-randomForest(BinaryY~., data=Xvars, trees=51, mtry=5, seed=200)
predict(test1, newdata=cbind(NewBinaryY, NewXs), type="response")
and this code:
set.seed(100)
test2<-randomForest(BinaryY~., data=Xvars, trees=51, mtry=5, seed=200,
xtest=NewXs, ytest=NewBinarY)
The
2018 Jan 17
4
Random Forests
Buenas tardes a todos. El paquete randomForest tiene la función
treesize, que es el nº de nodos. Me dan valores realmente elevados (en
torno a 1000), y eso me parece extraño. ¿sabéis si es así?
Gracias,
Manuel
--
Dr Manuel Mendoza
Department of Biogeography and Global Change
National Museum of Natural History (MNCN)
Spanish Scientific Council (CSIC)
C/ Serrano 115bis, 28006 MADRID
Spain
2012 Jan 27
1
Bivariate Partial Dependence Plots in Random Forests
Hello,
I was wondering if anyone knew of an R function/R code to plot bivariate
(3 dimensional) partial dependence plots in random forests (randomForest
package).
It is apparently possible using the rgl package
(http://esapubs.org/archive/ecol/E088/173/appendix-C.htm) or there may
be a more direct function such as the pairplot() in MART (multiple
additive regression trees)?
Many
2018 Jan 20
2
Random Forests
Si, Carlos. Yo hago lo mismo, pero esos mismos numeritos salen enormes.
> treesize(RFfit)
[1] 4304 4302 4311 4319 4343 4298 4298 4311 4349 4327 4331 4317
4294 4321 4283 4362
[17] 4300 4330 4266 4331 4308 4352 4294 4315 4372 4349 4331 4347
4329 4348 4298 4335
[33] 4346 4396 4345 4313 4293 4276 4353 4272 4304 4325 4317 4336
4308 4351 4374 4324
[49] 4386 4359 4311 4346 4300
2004 Mar 02
1
some question regarding random forest
Hi,
I had two questions regarding random forests for regression.
1) I have read the original paper by Breiman as well as a paper
dicussing an application of random forests and it appears that the one
of the nice features of this technique is good predictive ability.
However I have some data with which I have generated a linear model
using lm(). I can get an RMS error of 0.43 and an R^2 of
2018 Jan 22
2
Random Forests
Muchas gracias Carlos, como siempre.
Es raro que se me pasase. En su momento miré todos los argumentos del
RF, como hago siempre, pero ese lo había olvidado. La verdad es que
funcionaba estupendamente, pero me parecía extraño. Aunque dado que
los RF no sobreajustan, no hay problema con que sus árboles sean todo
lo grandes que quieras. Lo he testado con una base de datos externa y
explica
2006 Jul 23
1
Iterated Data Input/Output with Random Forests
Hi,
I am currently writing code to input a few thousand files, run them through the
Random Forests package, and then output corresponding results.
When I use the code below:
zz<-textConnection("ex.lm.out", "w")
sink(zz)
2007 Jan 29
3
comparing random forests and classification trees
Hi,
I have done an analysis using 'rpart' to construct a Classification Tree. I
am wanting to retain the output in tree form so that it is easily
interpretable. However, I am wanting to compare the 'accuracy' of the tree
to a Random Forest to estimate how much predictive ability is lost by using
one simple tree. My understanding is that the error automatically displayed
by the two
2008 May 05
1
Count data in random Forest
Hello R-user!
I am running R 2.7.0 on a Power Book (Tiger). (I am still R and
statistics beginner)
I try to find the most important variables to divide my dataset as
given in a categorical variable using randomForest.
Is randomForest() able to deal with count data?
Or is there no difference because only the ranks are used in the trees?
Thanks in advance
Birgit
Birgit Lemcke
Institut f?r
2012 Apr 10
1
Help predicting random forest-like data
Hi,
I have been using some code for multivariate random forests. The output
from this code is a list object with all the same values as from
randomForest, but the model object is, of course, not of the class
randomForest. So, I was hoping to modify the code for predict.randomForest
to work for predicting the multivariate model to new data. This is my
first attempt at modifying code from a
2009 Apr 20
1
Random Forests: Predictor importance for Regression Trees
Hello!
I think I am relatively clear on how predictor importance (the first
one) is calculated by Random Forests for a Classification tree:
Importance of predictor P1 when the response variable is categorical:
1. For out-of-bag (oob) cases, randomly permute their values on
predictor P1 and then put them down the tree
2. For a given tree, subtract the number of votes for the correct
class in the
2007 Dec 18
1
Random forests
Dear all,
I would like to use a tree regression method to analyze my dataset. I
am interested in the fact that random forests creates in-bag and
out-of-bag datasets, but I also need an estimate of support for each
split. That seems hard to do in random forests since each tree is
grown using a subset of the predictor variables.
I was thinking of setting mtry = number of predictor variables,
2010 Aug 06
1
Error on random forest variable importance estimates
Hello,
I am using the R randomForest package to classify variable stars. I have
a training set of 1755 stars described by (too) many variables. Some of
these variables are highly correlated.
I believe that I understand how randomForest works and how the variable
importance are evaluated (through variable permutations). Here are my
questions.
1) variable importance error? Is there any ways
2010 Oct 22
2
Random Forest AUC
Guys,
I used Random Forest with a couple of data sets I had to predict for binary
response. In all the cases, the AUC of the training set is coming to be 1.
Is this always the case with random forests? Can someone please clarify
this?
I have given a simple example, first using logistic regression and then
using random forests to explain the problem. AUC of the random forest is
coming out to be
2009 Mar 20
1
Pruning trees in a Random Forest
Hi all!
The randomForest in R enables us to prune the trees using the nodesize
feature where we can stop splitting a node if it contains less than the
specified no.of of records/entities at that node.
However is there a way to stop the tree growing after a specified number of
levels. To be more clear on what I mean by a level. Level 0 is the parent
node, Level 1 has 2 daughter nodes, Level 2 has