Displaying 20 results from an estimated 12000 matches similar to: "Multiple regression trees"
2001 Nov 28
2
Value lables, variable lables
I'm looking for an analogy to SPSS and "variable lable" and "value
lable" in R. I have a copy of S+4.0 and can't find any info in their
docs, and don't find it in R-intro either.
In SPSS, for each variable, there is a name like
VAR001
and a variable lable (a longer descriptive string) like
Respondent ID
and for many of the values of other variables there are
2009 Jul 26
3
Question about rpart decision trees (being used to predict customer churn)
Hi,
I am using rpart decision trees to analyze customer churn. I am finding that
the decision trees created are not effective because they are not able to
recognize factors that influence churn. I have created an example situation
below. What do I need to do to for rpart to build a tree with the variable
experience? My guess is that this would happen if rpart used the loss matrix
while creating
2012 Jul 06
2
Plotting rpart trees with long list of class members
I have a class with 732 members, so using rpart.plot is giving me a tiny plot
in the middle of the window. Is there a good way to modify the plot, or
replace the long list with something like "group1"?
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2004 Mar 19
2
How to collect trees grown by rpart
Jonathan,
Try making a list instead of an array. See ?list. Also, did you look into
random forests? I'm not sure what you want to do, but there might be
methods there to do some of the work for you.
Sean
On 3/19/04 1:12 PM, "Jonathan Williams"
<jonathan.williams at pharmacology.oxford.ac.uk> wrote:
> I would like to collect the trees grown by rpart fits in an array,
2005 Aug 14
1
How to add decision trees into a list?
Hi,
I am somewhat new to R so this question may be
foolish, but is it possible to add decision trees into
a list, array or vector in R?
I am trying to build a collection (ensemble) of
decision trees. Every time a new instance arrive I
need to get the prediction of each decision tree. I
have tried to add a decision tree into a variable but
without luck. Is a special package needed perhaps?
This
2012 Mar 05
1
decision/classification trees with fewer than 20 objects
Hi!
I'm trying to construct and plot a decision tree to class a set of only 8 objects and tried to use the rpart and tree function, but get a error message both times:
rpart: fit is not a tree, just a root
tree: cannot plot singlenode tree
I read in the post 'question regression trees' that rpart doesn't split a set of fewer than 20 objects...so I guess the same holds true for
2002 Jan 28
4
Multivariate response trees
I would like to know if someone has done work on trees with
multivariate response. I need something like rpart but for vector
responses. If someone has code that he/she is willing to share, I
would be grateful. If not, even guidelines for writing my own starting
from rpart would be welcomed.
ft.
--
Fernando TUSELL e-mail:
Departamento de
2007 Feb 02
2
Regression trees with an ordinal response variable
Hi,
I am working on a regression tree in Rpart that uses a continuous response
variable that is ordered. I read a previous response by Pfr. Ripley to a
inquiry regarding the ability of rpart to handle ordinal responses in
2003. At that time rpart was unable to implement an algorithm to handle
ordinal responses. Has there been any effort to rectify this in recent
years?
Thanks!
Stacey
On
2011 Aug 08
1
Classification trees problem.
Hello Everyone,
I'm doing a Classification trees with categorical explanatory variables using library rpart and I would like to do a prediction for some data imputs. I don't know where's a function or how can I do it?. Is there someone can help ?? ¿. Here's the code that I'm using.
library(rpart)
fit <- rpart(Kyphosis ~ Age + Number + Start, data=kyphosis)
plot(fit)
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 Dec 17
1
pruning trees using rpart
Hi,
I am using the packages tree and rpart to build a classification tree to
predict a 0/1 outcome. The package rpart has the advantage that the function
plotcp gives a visual representation of the cross-validation results with a
horizontal line indicating the 1 standard error rule, i.e. the
recommendation to select the most parsimonious model (the smallest tree)
whose error is not more than one
2004 Mar 08
3
Decision Trees
I am familiar with the rpart and tree packages for classification and
regression trees. However, quite a bit of the research in the
transportation community relating to decision trees uses the C4.5 family of
algorithms by Quinlan. Are there any plans to make a C4.5 (or a derivative
of it) available to R? If not, then I might use the WEKA Java package (
http://www.cs.waikato.ac.nz/ml/weka) that
2009 Nov 30
3
rpart: how to assign observations to nodes in regression trees
Hi,
I am building a regression tree (method=anova) by using rpart package
and as a final result I get the final leaves characterized by
different means and standard deviations for the dependent variable.
However, differently from the classification tree for categorical
variables I cannot find a way to assign each observation to a leaf,
i.e. I can find no frame whcih contains the observation id
2007 Feb 28
1
question regression trees
Hello,
This is my first time addressing such a big audience so apologies in
advance in case I fail to formulate this question.
I am working with 13 species of trees, and the data I have are:
1 continuous (phenolic concentration in xylem and in phloem) and 2
categorical variables: lineage (3 subclades) and habitat (fire and non
fire).
I am trying to see how species can be splitted
2005 Aug 26
2
learning decision trees with one's own scoring functins
Hi netters,
I want to learn a decision tree from a series of instances (learning data).
The packages
tree or rpart can do this quite well, but the scoring functions (splitting
criteria) are
fixed in these packages, like gini or something. However, I'm going to use
another scoring
function.
At first I wanna modify the R code of tree or rpart and put my own scoring
function in. But it
2001 May 22
1
Surrogate splits for decision trees
Dear R,
Short verse of the question:
Is there R code which will calculate surrogate splits
and/or delta impurity for decision trees at each node?
Long Version:
I have local, legacy code which I use to calculate my decision trees.
I would like to switch to R, but as I understand it surrogate splits
are not implemented.
Surrogate splits and feature ranking are described in Breiman et al
2009 Dec 16
2
rcart - classification and regression trees (CART)
Hi,
I am trying to use CART to find an ideal cut-off value for a simple
diagnostic test (ie when the test score is above x, diagnose the condition).
When I put in the model
fit=rpart(outcome ~ predictor1(TB144), method="class", data=data8)
sometimes it gives me a tree with multiple nodes for the same predictor (see
below for example of tree with 1 or multiple nodes). Is there a way
2010 Dec 14
1
rpart - how to estimate the “meaningful” predictors for an outcome (in classification trees)
Hi dear R-help memebers,
When building a CART model (specifically classification tree) using rpart,
it is sometimes obvious that there are variables (X's) that are meaningful
for predicting some of the outcome (y) variables - while other predictors
are relevant for other outcome variables (y's only).
*How can it be estimated, which explanatory variable is "used" for which of
2008 Mar 04
1
Difficulty labeling plot axis when "mar" and "oma" are set
Dear all,
Though labeling the x and y axis in the plot command seems to be straight
forward, I can not get it to work if I do the following:
## Creating example data
edata <- c(1,2,1,2)
edata <- matrix(edata, 2, 2, byrow = T)
colnames(edata) <- c("a", "b")
edata <- data.frame(edata)
## plot data
par(mfrow<- c(1,2))
plot(edata$a, edata$b, xlab =
2011 Jan 24
1
How to measure/rank ?variable importance when using rpart?
--- included message ----
Thus, my question is: *What common measures exists for ranking/measuring
variable importance of participating variables in a CART model? And how
can
this be computed using R (for example, when using the rpart package)*
---end ----
Consider the following printout from rpart
summary(rpart(time ~ age + ph.ecog + pat.karno, data=lung))
Node number 1: 228 observations,