> On 24 May 2017, at 04:38 , Bert Gunter wrote:
>
> 1. Forget Excel. Erase it from your memory. banish its paradigms from
> your practices. Faiing to do so will only bring misery as you explore
> R. R is a rational programming language primarily for data analysis,
> statistics, and graphics. Exc
Hi,
I am using rpart to build a decision tree, I am then using printcp to find
the cross-validation error (xerror) of different splits of the decision
tree.
I was wondering how I can use the rpart package to find sensitivity (false
negative) and specificity (false positive) of cross-validation fo
io, reload it and try again.
John Kane
Kingston ON Canada
-Original Message-
From: jcthomp...@redlobster.com
Sent: Tue, 28 Jun 2016 20:26:59 +
To: r-help@r-project.org
Subject: [R] Rpart plot produces no text
I am using R Studio and am able to fit a tree with RPlot, however, the
tree in
nal Message-
> From: jcthomp...@redlobster.com
> Sent: Tue, 28 Jun 2016 20:26:59 +
> To: r-help@r-project.org
> Subject: [R] Rpart plot produces no text
>
> I am using R Studio and am able to fit a tree with RPlot, however, the
> tree in the viewer has no text (see i
I am using R Studio and am able to fit a tree with RPlot, however, the tree in
the viewer has no text (see image attached).
Jim Thompson
This e-mail message is for the sole use of the intended recipient and may
contain information that is confidential, proprietary or privileged. Any
unauthorize
Dear R users
I have a question regarding rpart and survey weights. In the introduction
to rpart document it says "Weights are not yet supported, and will be
ignored if present", however they are somehow used as the results are
different with and without weights. Can weights now be used and if yes,
Thank you so much for the clarification Terry.
On Thu, Oct 8, 2015 at 6:03 PM, Therneau, Terry M., Ph.D. wrote:
> The cutpoint is on the predictor, so the interpretation is the same as it
> is for any other rpart model. The subjects with predictor < cutpoint form
> one group and those > cutpoin
The cutpoint is on the predictor, so the interpretation is the same as it is for any other
rpart model. The subjects with predictor < cutpoint form one group and those > cutpoint
the other. The cutpoint is chosen to give the greatest difference in "average y" between
the groups. For poisson "
Hi All,
I am trying to derive cutpoint/threshold with a poisson distributed
dependent variable. I know how to interpret cutpoint with binary dependent
variable based on direction. Can some on help me to intrepret cutpoint for
poisson case with one independent variable with the derived threshold.
OK thanks
That works.
:)
Ô__
c/ /'_;kmezhoud
(*) \(*) ⴽⴰⵔⵉⵎ ⵎⴻⵣⵀⵓⴷ
http://bioinformatics.tn/
On Thu, Nov 13, 2014 at 10:41 PM, William Dunlap wrote:
> Use paste(collapse="\n", junk) if you want it as a single string with \n's
> in it.
>
> Bill Dunlap
> TIBCO Software
> wdunlap tibco
Use paste(collapse="\n", junk) if you want it as a single string with \n's
in it.
Bill Dunlap
TIBCO Software
wdunlap tibco.com
On Thu, Nov 13, 2014 at 1:13 PM, Karim Mezhoud wrote:
> Yes Thanks! that works,
> but I loose the \n when I would like to save or edit it.
>
> getTextInWindows is a fun
Yes Thanks! that works,
but I loose the \n when I would like to save or edit it.
getTextInWindows is a function that edits any text in editor.
getTextInWindows(summary): without "\n"
save (file= "junk.txt", junk):without "\n"
getTextInWindow(capture.output(cat(junk, sep = "\n"))) :No works
Thank
Use capture.output(), as in
> junk <- capture.output(summary(1:10))
> junk
[1] " Min. 1st Qu. MedianMean 3rd Qu.Max. "
[2] " 1.003.255.505.507.75 10.00 "
> cat(junk, sep="\n")
Min. 1st Qu. MedianMean 3rd Qu.Max.
1.003.255.505.5
Hi,
All right for rpart package but it seems there is a confusion in "text"
function.
prp is not found
Error in fun() : could not find function "prp"
Thanks
Ô__
c/ /'_;kmezhoud
(*) \(*) ⴽⴰⵔⵉⵎ ⵎⴻⵣⵀⵓⴷ
http://bioinformatics.tn/
[[alternative HTML version deleted]]
___
Hi,
the print of rpart fitting gives the summary of tree
I would like to save the console text of:
fit <- rpart(formula, data)
summary <- print(fit)
when I look in "summary" I did not find the same thing as in
"print(rpart)"
[1] "Clinical Data exists"
[1] "merging samples from Clinical an
un...@r-project.org>
[mailto:r-help-boun...@r-project.org] On Behalf Of Schillo, Sonja
Sent: Thursday, April 03, 2014 3:58 PM
To: Mitchell Maltenfort
Cc: r-help@r-project.org<mailto:r-help@r-project.org>
Subject: Re: [R] rpart and randomforest results
Hi,
the random forest should do that,
Sent: Thursday, April 03, 2014 3:58 PM
To: Mitchell Maltenfort
Cc: r-help@r-project.org
Subject: Re: [R] rpart and randomforest results
Hi,
the random forest should do that, you're totally right. As far as I know it
does so by randomly selecting the variables considered for a split (but here w
" from the randomforest away.
Is that plausible and does anyone have another idea?
Thanks
Sonja
Von: Mitchell Maltenfort [mailto:mmal...@gmail.com]
Gesendet: Dienstag, 1. April 2014 13:32
An: Schillo, Sonja
Cc: r-help@r-project.org
Betreff: Re: [R] rpart and randomforest results
Is it possible
Is it possible that the random forest is somehow adjusting for optimism or
overfitting?
On Apr 1, 2014 7:27 AM, "Schillo, Sonja" wrote:
> Hi all,
>
> I have a question on rpart and randomforest results:
>
> We calculated a single regression tree using rpart and got a pseudo-r2 of
> roundabout 10%
Hi all,
I have a question on rpart and randomforest results:
We calculated a single regression tree using rpart and got a pseudo-r2 of
roundabout 10% (which is not too bad compared to a linear regression on this
data). Encouraged by this we grew a whole regression forest on the same data
set u
I am trying to export the tree splitting results from a rpart object. I
can visualize the splits by printing the rpart object (shown below for my
rpart object, model.prune). However, this printed result is not a
dataframe and I am unable to export this information in .csv format.
I can view the
Carol,
Actually, you have only five nodes, numbered 1, 2, 3, 6, and 7.
And all five nodes are included in your plot.
Nodes 1 and 3 are branching nodes; nodes 2, 6, and 7 are terminal nodes.
Try typing just the name of the rpart object for a very brief text version
of the tree.
rpart.res
Jea
Hi,
When I look at the summary of an rpart object run on my data, I get 7 nodes but
when I plot the rpart object, I get only 3 nodes. Should the number of nodes
not match in the results of the 2 functions (summary and plot) or it is not
always the same?
Look forward to your reply,
Carol
--
I know that rpart has a complexity parameter that adjusts the number of nodes
in a model. I also know that a loss function allows one to weight
misclassifications of different types. However, some of my predictor variables
are much more expensive dollar-wise to use than others. Is there a way to
On 18.08.2012 21:32, Daniel Blankenheim wrote:
Hey
my name is daniel, i am writing my bachelor thesis and wondering if you can
help me.
i am trying to generate a regression tree via rpart. to
reduce the error of the model i use cross validation, but instead
of reducing the cross validation er
Hey
my name is daniel, i am writing my bachelor thesis and wondering if you can
help me.
i am trying to generate a regression tree via rpart. to
reduce the error of the model i use cross validation, but instead
of reducing the cross validation error (xerror) is increasing the more splits
there ar
Jean,
Thanks for your quick reply and suggestions!
> In the help file for predict.rpart it says, "The predictors referred to in
> the right side of formula(object) must be present by name in newdata."
I was aware of that statement from the help file. I wondered about the
reason for that require
Jason,
In the help file for predict.rpart it says, "The predictors referred to in
the right side of formula(object) must be present by name in newdata."
?predict.rpart
So, that's just the way it is. There are a couple ways to work around
this, if you wish. You could create a data frame with a
After fitting and pruning an rpart model, it is often the case that one or
more of the original predictors is not used by any of the splits of the
final tree. It seems logical, therefore, that values for these "unused"
predictors would not be needed for prediction. But when predict() is called
on s
Replying to quite old thread..but its awesome
RWeka package is quite good in dissecting the tree in more than 2 parts.
As someone said J48 which is implementation of C4.5 and thus ID3 will be
helpful.
Also to plot you may have to rage a war like situation.
Let us knoe if you face any problem
On 28/05/2012 08:27, Jeff Newmiller wrote:
It is isn't easy to write code that works with column names that have spaces. You could
rewrite rpart, or just rename the columns in your data frame to work around the
"bug". See ?names.
In any case, rpart pre-dates the `` notation that made this pos
It is isn't easy to write code that works with column names that have spaces.
You could rewrite rpart, or just rename the columns in your data frame to work
around the "bug". See ?names.
---
Jeff Newmiller
Hi,
Our data has column names with spaces in that.The names in dataFrame are,
*[1] "Sepal Length" "Sepal Width" "Petal Length" "Petal Width"
"Species" *
When i try to use the column names in rpart function, it gives the following
error.
* rp<-rpart(as.factor(`Species`)~`Sepal Length`)
Erro
Hi Uwe:
Thanks a lot for your reply.
I contemplated the use of the predict() function but realized that it could
not return what I needed (i.e., the terminal nodes and not the classes). I
went back to the post of Professor Ripley
(http://tolstoy.newcastle.edu.au/R/e4/help/08/07/17702.html) and
On 15.05.2012 16:30, tudor wrote:
Dear useRs:
Is there a way I could predict the terminal node associated with a new data
entry in an rpart environment? In the example below, if I had a new data
entry with an AM of 5, I would like to link it to the terminal node 2. My
searches led to http://to
Dear useRs:
Is there a way I could predict the terminal node associated with a new data
entry in an rpart environment? In the example below, if I had a new data
entry with an AM of 5, I would like to link it to the terminal node 2. My
searches led to http://tolstoy.newcastle.edu.au/R/e4/help/08/07
On Apr 3, 2012, at 4:16 AM, Raji wrote:
Hi R-helpers,
I am using rpart package for decision tree using R.We are invoking R
environment through JRI from our java application.Hence, the result
of R
command is returned in REXP and we use geterrMessage() to retrieve the
error.
When we execute t
Hi R-helpers,
I am using rpart package for decision tree using R.We are invoking R
environment through JRI from our java application.Hence, the result of R
command is returned in REXP and we use geterrMessage() to retrieve the
error.
When we execute the following command,
cnr_model<-rpart(as.fac
Dear All,
if I use rpart to built a regression tree and if I study the spatial
autocorrelation of the residuals of regression tree, how I use Moran test
(or other test) on these residuals?
Moran's Test work on lm object, but I have a rpart object.
thanks,
Myriam
[[alternative HTML version
On Wed, 15 Feb 2012, dlofaro wrote:
Dear R-Users,
I'm a R beginner and I have a similar problem:
I fitted a SurvivalTree with rpart and I'm tryng to plot with the partykit
package by the funcion as.party but it sends me this error:
plot(as.party(rpartSurv))
Error in plot.constparty(as.party(r
Dear R-Users,
I'm a R beginner and I have a similar problem:
I fitted a SurvivalTree with rpart and I'm tryng to plot with the partykit
package by the funcion as.party but it sends me this error:
> plot(as.party(rpartSurv))
Error in plot.constparty(as.party(rpartSurv)) :
node_surv not yet imple
On 10.02.2012 10:37, MYRIAM TABASSO wrote:
Dear All,
I have questions about the function "rpart" to construct a regression tree
in
R code.
My problem is how to change the splitting criteria.
In the "rpart" we have : parms=list(split="..") , I ask you if in this
command is it possible to u
Dear All,
I have questions about the function "rpart" to construct a regression tree
in
R code.
My problem is how to change the splitting criteria.
In the "rpart" we have : parms=list(split="..") , I ask you if in this
command is it possible to use an another splitting criterion to substitute
Stephen: I tried running your script but couldn't make it work (any feedback
is welcome) so I changed it a little bit. I found you still need to set the
# of digits as the max # of possible digits of your yval response or
greater.
node.fun <- function(x)
{
x$frame$yval<-as.integer(sprintf("%0.f
I'm inspecting tests/usersplits.R in rpart, trying to get my head around how
to pass data to the split function.
I'm trying to instantiate a number of goodness measures which compare
treatment vs control within splits.
A simple example is difference-in-difference estimate of a candidate split,
Hi Amanda,
Sorry for the bit of a slow response (classes and research have been
chaotic). Below are details on what I looked at and a few suggestions
at the end for what you can do.
To the general R community: summary.rpart() makes explicit the default
dropping behavior of `[` which makes me thi
Hi Everyone,
I'm working on building some classification trees, and up to this point
I've been using rpart. However, I recently discovered the tree package,
and found that it had some useful functions (in particular deviance(),
which I would really like to use for my project). I can't seem to
Hi Amanda,
Can you reproduce the error with a small subset of the data? If so,
could you send it to us? For instance if say 20 cases is sufficient,
you could send the output of dput() which pastes easily into the
console:
dput(yourdata[, c("ENROLL_YN", "MINORITY")])
You could also try calling
We are trying to make a decision tree using rpart and we are continually
running into the following error:
> fit_rpart=rpart(ENROLL_YN~MINORITY,method="class")
> summary(fit_rpart)
Call:
rpart(formula = ENROLL_YN ~ MINORITY, method = "class")
n= 5725
CP nsplit rel error
1 0 0 1
Hi all,
I am very new to R (only two days of studies). I know a little bit of
statistical learning and looking for an implementation of CART and random
forest and therefore I am now studying R.
I tested with rpart and randomForest package, they are quite good.
However, I need a classification
This mostly happens when the data contain invalid column names (such as all
numbers). Try using make.names() on the datasets.
Max
On Oct 30, 2011, at 11:35 AM, Luisa Sêco wrote:
> Dear users,
>
> I'm using rpart for classification trees, but my code isn't working when I
> try to use all the
Dear users,
I'm using rpart for classification trees, but my code isn't working when I
try to use all the variables in my data frame. This data frame was created
from a data frame with 1775 variables, but I choose only 13.
arv13<-rpart(iv~.,data=gn,method="class",parms=list(split="information"))
On Thu, 8 Sep 2011, Carlos Ortega wrote:
Hi,
Use packages "rpart.plot" or "maptree" to enhance the tree drawing.
Or another alternative, use "party" package that offers much more graphing
possibilities.
There is also the "partykit" package on R-Forge which offers party-style
graphics for rpa
"Brian Jensvold" het geskryf
I am trying to create a classification tree using either tree or rpart
but when it comes to plotting the results the formatting I get is
different than what I see in all the tutorials. What I would like to
see is the XX/XX format but all I get is a weird decimal val
Hi,
Use packages "rpart.plot" or "maptree" to enhance the tree drawing.
Or another alternative, use "party" package that offers much more graphing
possibilities.
Regards,
Carlos Ortega
www.qualityexcellence.es
On Thu, Sep 8, 2011 at 5:27 PM, Brian Jensvold wrote:
> I am trying to create a cla
I am trying to create a classification tree using either tree or rpart
functions but when it comes to plotting the results the formatting I get is
different than what I see in all the tutorials (like
http://www.youtube.com/watch?v=9XNhqO1bu0A or
http://www.youtube.com/watch?v=m3mLNpeke0I&feature=re
-- begin included message --
I am trying to create a classification tree using either tree or rpart
but when it comes to plotting the results the formatting I get is
different than what I see in all the tutorials. What I would like to
see is the XX/XX format but all I get is a weird decimal value.
I am trying to create a classification tree using either tree or rpart
but when it comes to plotting the results the formatting I get is
different than what I see in all the tutorials. What I would like to
see is the XX/XX format but all I get is a weird decimal value. I was
also wondering how yo
Jay het geskryf
When I have made a decision tree with rpart, is it possible to "apply"
this tree to a new set of data in order to find out the distribution
of observations? Ideally I would like to plot my original tree, with
the counts (at each node) of the new data.
Sadly, neither plot.rpart
I tried that, while I find the documentation a bit short, but the only
result I get from this is a probability distribution of my data (I'm
building a tree with 2 classes). How do I plot a tree where the counts
are show in each step/node?
BR,
Jay
On Aug 29, 9:40 pm, Weidong Gu wrote:
> ? predict
Hello everyone,
I working in a public health project and we have created a Decision Tree for
categorical variables usign the package rpart. Our goal is to develop a model
(Using the ROC tool) in order to predict presence/ausent of diabetes and get a
better understanding of what are the import
? predict.rpart
Weidong Gu
On Mon, Aug 29, 2011 at 12:49 PM, Jay wrote:
> Hi,
>
> when I have made a decision tree with rpart, is it possible to "apply"
> this tree to a new set of data in order to find out the distribution
> of observations? Ideally I would like to plot my original tree, with
>
Hi,
when I have made a decision tree with rpart, is it possible to "apply"
this tree to a new set of data in order to find out the distribution
of observations? Ideally I would like to plot my original tree, with
the counts (at each node) of the new data.
Reagards,
Jay
_
Jay wrote:
While I'm very pleased with the results I get with rpart and
rpart.plot, I would like to change the scientific notation of the
dependent variable in the plots into integers. Right now all my 5 or
more digit numbers are displayed using scientific notation.
One way of getting rpart.pl
On Aug 25, 2011, at 10:38 AM, Jean V Adams wrote:
I don't see a quick solution to this.
You could contact the maintainer of the rpart.plot package, Stephen
Milborrow
maintainer("rpart.plot")
or you could try to modify the rpart.plot() function yourself to
meet your
needs
rpart.pl
I don't see a quick solution to this.
You could contact the maintainer of the rpart.plot package, Stephen
Milborrow
maintainer("rpart.plot")
or you could try to modify the rpart.plot() function yourself to meet your
needs
rpart.plot
Jean
Jay wrote on 08/25/2011 05:30:25 AM:
>
>
While I'm very pleased with the results I get with rpart and
rpart.plot, I would like to change the scientific notation of the
dependent variable in the plots into integers. Right now all my 5 or
more digit numbers are displayed using scientific notation.
I managed to find this:
http://tolstoy.new
Thank you for all your help. The unexpected solution to my predict()
problem was to use the Misc menu and remove all objects before
proceeding further. The final digits of the trees continue to be
clipped but I can live with that.
Mark
__
R-help@r-pr
Hi,
I have been working generating decision tree analyses on large numbers of
simulation datasets using the RPART function. With some datasets, RPART is
returning an error of "Error in yval[, 1] : incorrect number of dimensions".
There seem to be certain types of splits that cause it to break
Dear Tal and Achim:
Thank you both for your assistance.
I followed Achim's suggestions and got what I needed on a Windows machine
with R2.12.2 installed. As I needed to run the task on a Windows machine
with R2.11.1 I used the package rpart.plot (by Stephen Milborrow) to create
my charts.
Best
Hi Tal:
Thanks for your quick reply.
I tried to create a classification tree.
The problem is that the branches overlap the text in the ellipses (inner
nodes) and rectangles (terminal nodes) - At times this makes it difficult
for the reader to correctly process the results. One way to overcome
Hi Achim:
I will give it a try and let you know how it goes.
Thanks.
Tudor
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__
R-help@
On Fri, 8 Apr 2011, tudor wrote:
Dear useRs:
I try to plot an rpart object but cannot get a nice tree structure plot. I
am using plot.rpart and text.rpart (please see below) but the branches that
connect the nodes overlap the text in the ellipses and rectangles. Is there
a way to get a clean
Hi Tudor,
What type of tree did you create? (classification or regression?)
Could you give an explanation as to what is not looking nice?
Contact
Details:---
Contact me: tal.gal...@gmail.com | 972-52-7275845
Read me: www.talgal
Dear useRs:
I try to plot an rpart object but cannot get a nice tree structure plot. I
am using plot.rpart and text.rpart (please see below) but the branches that
connect the nodes overlap the text in the ellipses and rectangles. Is there
a way to get a clean nice tree plot (as in the Rpart Mayo
Hey everyone,
So I am looking for a way to create a decision tree for a modeling class and
I am not all that familiar with R. I thought I might be able to use RPart,
but I can't get it to work. I want a simple tree with a parent that says the
amount and each child has a percentage of likelyhood an
Hello Xiaogang, and thank you for your answer.
Your solution was indeed the way I had considered taking (after consulting
with some friends in my lab), however, I had hoped to find out if this
information (what variable effects which outcome variable) was somehow
implicitly contained within the rp
Hi, Tal,
Here is a quick way of getting around. First create two responses via
dummy variables
y1 <- ifelse(y=="a", 1, 0)
y2 <- ifelse(y=="b", 1, 0)
and then built two separate tree models for y1 and y2 separately.
Hope it helps.
Xiaogang
On Tue, Dec 14, 2010 at 8:33 AM, Tal Galili wrote:
>
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 onl
s the room still a room when its empty? Does the room,
the thing itself have purpose? Or do we, what's the word... imbue it."
- Jubal Early, Firefly
r-help-boun...@r-project.org wrote on 12/02/2010 05:34:23 AM:
> [image removed]
>
> [R] rpart results - problem after overs
Hi all,
I am trying to predict a target variable that takes values 0 or 1 using the
rpart command. In my initial dataset I have few positive observations of the
target variable; therefore I have oversampled the rare event by a multiple of 6
(i.e. from 762 to 4572).
However, in my results, I en
Here is the complete dataset:
Outlook TempHumidityWindy Class
Sunny 2 2 Yes Play
Sunny 2 1 Yes Don't Play
Sunny 3 1 No Don't Play
Sunny 2 1 No Don't Play
Sunny 1 2 No Play
Overcast2
@Above,
Thanks. That certainly helps.
I understand that the rpart splits only in binary. Is there any support in R
to make the split have more than 2 nodes?
Cheers,
Jagdeesh
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On Mon, 11 Oct 2010, jagdeesh_mn wrote:
Hi,
Being a novice this is my first usage of R.
I am trying to use rpart for building a decision tree in R. And I have the
following dataframe
Outlook TempHumidityWindy Class
Sunny 75 70 Yes Play
Sunny 80 90 Y
Or now Im pretty sure of it as when I took your dataset and used the magic
way of ctrl-c ctrl-v to make some more observations I get a decision tree.
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My guess is that you have two few observations is your dataset for rpart to
determin a "safe" dissision.
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___
Dont know if it will work but you can try ctree from the party package
require(party)
bla <- ctree(Class ~ Outlook + Temp + Humidity + Windy, data=dataframe)
plot(bla)
//Joel
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Hi,
Being a novice this is my first usage of R.
I am trying to use rpart for building a decision tree in R. And I have the
following dataframe
Outlook TempHumidityWindy Class
Sunny 75 70 Yes Play
Sunny 80 90 Yes Don't Play
Sunny 85 85
Hi All,
I am fitting a tree to censored survival data using the rpart package and
wanted to better understand the results.
I am trying to interpret the output from the tree. I am interested in
understanding what "yval" is for a survival tree. I see in the output of
summary, the phrase "estimated
Hi Olga,
not directly related to your question. We have also a server
installation and subsequently our IT department determines which version
and packages I can use on R.
A few days ago I have switched to R-portable. Works without any problems
from my USB stick on any locked-for-installation W
Olga Shaganova wrote:
Hi,
I am a brand new user and may be my question is too simple. I have R on
our (not Unix) server. I am trying to build a decision tree and the error
message says "couldn't find function rpart". Does it mean I have to ask our
server guy to install an additional package?
Hi,
I am a brand new user and may be my question is too simple. I have R on
our (not Unix) server. I am trying to build a decision tree and the error
message says "couldn't find function rpart". Does it mean I have to ask our
server guy to install an additional package?
Thank you,
Olga
[
This is just one single decision tree, not forest. If you're asking what
package I use to construct one single tree, it's 'rpart'.
>
>From: Changbin Du
>To: "Shi, Tao"
>Cc: r-help@r-project.org
>Sent: Fri, May 14, 2010 12:35:20 PM
>Subject
is this random decision tree, I dont know is there any package can run it.
If you know, please let me know.
On Fri, May 14, 2010 at 10:23 AM, Shi, Tao wrote:
> Hi list,
>
> Is there a way in "rpart" to force the variables only used once when doing
> the splits?
>
> This is how the question cam
Hi list,
Is there a way in "rpart" to force the variables only used once when doing the
splits?
This is how the question came about. Often time, the tree constructed uses the
same variable (say X1) for the first and second splits, for example. However,
due to practical reason, the researcher
On 03.05.2010 04:26, Claudia Penaloza wrote:
I ran this code (several times) from the Quick-R web page (
http://www.statmethods.net/advstats/cart.html) but my cross-validation
errors increase instead of decrease (same thing happens with an unrelated
data set).
Why does this happen?
Since the
I ran this code (several times) from the Quick-R web page (
http://www.statmethods.net/advstats/cart.html) but my cross-validation
errors increase instead of decrease (same thing happens with an unrelated
data set).
Why does this happen?
Am I doing something wrong?
# Classification Tree with rpar
Yes, outcome is there.
On Wed, Apr 21, 2010 at 3:47 PM, Steve Lianoglou <
mailinglist.honey...@gmail.com> wrote:
> Hi,
>
> On Wed, Apr 21, 2010 at 5:20 PM, Changbin Du wrote:
> > HI, Dear R community,
> >
> > Last friday, I used the codes, it works, but today, it does not run?
> >
> >
> >> fit.
Hi,
On Wed, Apr 21, 2010 at 5:20 PM, Changbin Du wrote:
> HI, Dear R community,
>
> Last friday, I used the codes, it works, but today, it does not run?
>
>
>> fit.dimer <- rpart(outcome ~., method="class", data=p.df)
> Error in `[.data.frame`(frame, predictors) : undefined columns selected
>
>
>
The Machine Learning Task view lists alternative packages you could try.
On Wed, Apr 21, 2010 at 5:20 PM, Changbin Du wrote:
> HI, Dear R community,
>
> Last friday, I used the codes, it works, but today, it does not run?
>
>
>> fit.dimer <- rpart(outcome ~., method="class", data=p.df)
> Error in
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