similar to: Re transaction list transformation to use rpart.

So there are a couple parts to this question. I am trying to implement the rpart/random forest algorithms on a transaction lists. That is to say i am trying to train models in order to deduce what are the most predictive transactions within a customers history in order apply this model to future test data and identify accounting irregularities(ie. this account had x and y so they should have also

Dear R users, I know cross-validation does not work in rpart with user defined split functions. As Terry Therneau suggested, one can use the xpred.rpart function and then summarize the matrix of the predicted values into a single "goodness" value. I need only a confirmation: set for example xval=10, if I correctly understood a single column of the matrix obatined by xpred.rpart gives

There have been various messages about packages tree and rpart whilst I have been travelling, and I have now prepared updates. tree ==== Tree is one of the oldest packages on CRAN (Feb 2000 apart from adding the maintainer field), and I had been hoping that it would fade away in favour of rpart. 1) sys.parent needed to be replaced by parent.frame in all but the most recent R (post 1.3.0).

All the documentation that I have on survival splitting is found in the technical report you mention. However, there is both a short form and a long form of this on our web site, did you get the larger one (52 pages)? I admit it is not a lot. There are no other split algorithms implimented for survival data. It would be possible to add your own. Attached is a slightly updated version of the

Yes, that seems like a sensible idea to me. Terry Therneau On Sat, 2011-12-03 at 12:00 +0100, r-help-request at r-project.org wrote: > The problem: There are no a priori groupings to run a classification > on > > My solution: > > This is a non-R code question, so I appreciate any thoughts. I have > used pam in the cluster package proceeded by sillohouette to find the

Hello Gurus: When I plot a survival fit using rpart for the classification tree, for each node, there is a decimal based number above the event/total. I tried to see if it's the exponential ratio or logrithmics, neither seem to be the case. I'm wondering if anyone knows what they are. Thanks, Karen _________________________________________________________________ Find hidden words,

On 08/14/2014 05:00 AM, r-devel-request at r-project.org wrote: > Dear list > > > For my work, it would be helpful if rpart worked seamlessly with an > empty model: > > library(rpart); rpart(formula=y~0, data=data.frame(y=factor(1:10))) > > Currently, an unrelated error (originating from na.rpart) is thrown. > > At some point in the near future, I'd like to

The question is about the direction vector in rpart. There are (at least) two preferred ways to lay out a tree, wrt the question of which obs are sent left and which right. 1. Send the smaller y values to the left. In the final tree, there will be a graphical ordering with smaller y's to the left and larger ones to the right. One has a "left bad, right good"

--- 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,

Dear all, I'm writing my own method to be used in Rpart by defining the list of functions named init, split and eval. I'm following the example given in the file 'tests/usersplits.R' in the sources. By now I'm able to define the split function (and it works correctly in the tree construction) while I have some problems with the init and the eval function. The task I'm

I don't know of one. If building your own you could use rpart with the "maxdepth=1" as the tool to find the best split at each node. Terry Therneau On 12/20/2012 05:00 AM, r-help-request at r-project.org wrote: > Hi, > > I've searched R-help and haven't found an answer. I have a set of data from which I can create a classification tree using > rpart. However,

I have created plots of rpart objects with the fancy option for text.rpart ("fancy" creates ellipses and rectangles and labels branches with splitting criteria). The ellipses and rectangles are supposed to "interrupt" the tree lines (as seen in Therneau and Atkinson 1997, page 48, Fig. 18, http://www.mayo.edu/hsr/techrpt/61.pdf), but they do not, even when I use Therneau and

I am using the package rpart to explore various classification structures. The call looks like: seekhi1<-rpart(pvol~spec+a1+psize+eppres+numpt+icds+bivalcrt+stents+ppshare+ nhosp+nyrs,data=dat,method="class", control=rpart.control(minsplit=30,xval=10)) The output is 1) root 198 87 1 (0.5606061 0.4393939) 2) psize=1,2 122 43 1 (0.6475410 0.3524590)

Hi, I've searched online, in a few books, and in the archives, but haven't seen this. I believe that xerror is scaled to rel error on the first split. After fitting an rpart object, is it possible with a little math to determine the percentage of true classifications represented by a xerror value? -seth -- View this message in context:

I've been using the package rpart with R 1.3.0 for Windows to produce simple classification trees for some measurement data from paleontological specimens. Both the rpart documentation and the output confirm that the program produces splits on continuous data that leave "holes" in the data. It is probably of little practical importance, but is there a reason why the binary

The package mvpart is now available. mvpart includes partitioning based on (1) multivariate numeric responses and (2) dissimilarity matrices. The package mvpart is a modification of rpart -- -- authors of original: Terry M Therneau and Beth Atkinson <atkinson at mayo.edu>, and R port of rpart Brian Ripley <ripley at stats.ox.ac.uk>. Includes some modified routines from vegan --

The package mvpart is now available. mvpart includes partitioning based on (1) multivariate numeric responses and (2) dissimilarity matrices. The package mvpart is a modification of rpart -- -- authors of original: Terry M Therneau and Beth Atkinson <atkinson at mayo.edu>, and R port of rpart Brian Ripley <ripley at stats.ox.ac.uk>. Includes some modified routines from vegan --

Dear R's I'm trying to use specific rather than random cross-validation groups in mvpart. The man page says: xval Number of cross-validations or vector defining cross-validation groups. And I found this reply to the list by Terry Therneau from 2006 The rpart function allows one to give the cross-validation groups explicitly. So if the number of observations was 10, you could use

When I run R CMD check on the survival package I invariably get a note: ... * checking for file ?survival/DESCRIPTION? ... OK * this is package ?survival? version ?3.2-6? * checking CRAN incoming feasibility ... NOTE Maintainer: ?Terry M Therneau <therneau.terry at mayo.edu>? ... This is sufficient for the auto-check process to return the following failure message: Dear maintainer,

I'm updating some (very) old code, and one particular option of its plot method depends on a once-was-true trick polygon(x, y, border=TRUE, col=0) polygon(x, y, border=TRUE, density=0) would draw the polygon AND erase whatever was underneath it back to background color. Is there a reliable way to do this with the current R (standard graphics)? Terry Therneau PS For the