search for: cptables

Hello list, I'm trying to generate classifiers for a certain task using several methods, one of them being decision trees. The doubts come when I want to estimate the cross-validation error of the generated tree: tree <- rpart(y~., data=data.frame(xsel, y), cp=0.00001) ptree <- prune(tree, cp=tree$cptable[which.min(tree$cptable[,"xerror"]),"CP"]) ptree$cptable

Deal R Users, I'm trying to find out how can I compute probabilities on a Bayesian Network using R. The Bayesian Network I modelled is shown at http://www.dsr.inpe.br/~mello/1727/BNgrapmodel.png and I'd like to know how can I proceed (commands on R) to answer questions like: (1) what is the probability of S=T given C=T, L=T, R=F, H=F and D=F; or (2) what is the probability of S=T

Can somebody save-me? Thanks in advance! #R script: #trying to find out how solve a discrete Bayesian Belief Network. #option: using 'catnet' package #BEGIN library(catnet) cnet <- cnNew(nodes = c("a", "b", "c"), cats = list(c("1", "2"), c("1", "2"), c("1", "2")), parents = list(NULL, c(1), c(1,

Howdy, I just did a git clone for the latest syslinux and when I entered the make command the build ended with an error. I also had to back level my git installation because "git clone url" doesn't seem to want to work any more yet it's what was on the web page. Regards, George... perl cptable.pl UnicodeData iso8859-8.txt iso8859-8.txt iso8859-8.cp perl cptable.pl

Dear R-devel, I am trying to alter rpart so that it makes additional calculations when growing the tree. In the "rpart.s" there is a call to the C routine: rp <- .C("s_to_rp2", as.integer(nobs), as.integer(nsplit), as.integer(nodes), as.integer(ncat),

Hi, I am reading the source code of rpart. I have problems understand the following code and would appreciate for any helps. In rpart.s, there is a line: rpfit &lt;- .C(C_s_to_rp, &nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; n = as.integer(nobs), &nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; &nbsp;&nbsp;&nbsp; nvarx

Hi, i am trying to compile latest development version of wine (1.1.23) on the new release of Fedora. I get this error during "make": make[1]: Entering directory `/home/v4mpiro/Scrivania/wine-1.1.23/tools' make[1]: `makedep' is up to date. make[1]: Leaving directory `/home/v4mpiro/Scrivania/wine-1.1.23/tools' make[1]: Entering directory

Hi All, I have to say upfront that I am a complete neophyte when it comes to programming. Nevertheless I enjoy the challenge of using R because of its incredible statistical resources. My problem is this .........I am running a regression tree analysis using "rpart" and I need to run the calculation repeatedly (say n=50 times) to obtain a distribution of results from which I will pick

...The kind of thing I hope to do is: > > resmat=array(NA, 100) > for (run in 1:100) resmat[run]=rpart(y~., data=train[run]) > > So that, later, I can do: > for (run in 1:100) pred[run]=predict(resmat[run], newdat) > > But, resmat[run] does not work, even though it saves the cptables. > > Thanks, in advance, > > Jonathan Williams > OPTIMA > Radcliffe Infirmary > Woodstock Road > OXFORD OX2 6HE > Tel +1865 (2)24356 > > ______________________________________________ > R-help at stat.math.ethz.ch mailing list > https://www.stat.math.ethz.c...

HI, Dear R community, I am writing the following function to create one data set(*tree.pred*) and one vector(*valid.out*) from loops. Later, I want to use the data set from this loop to plot curves. I have tried return, list, but I can not use the *tree.pred* data and *valid.out* vector. auc.tree<- function(msplit,mbucket) { * tree.pred<-data.frame()

Hello, I'm using mvpart option xv="1se" to compute a regression tree of good size with the 1-SE rule. To better understand 1-SE rule, I took a look on its coding in mvpart, which is : Let z be a rpart object , xerror <- z$cptable[, 4] xstd <- z$cptable[, 5] splt <- min(seq(along = xerror)[xerror <= min(xerror) + xvse * xstd]) I interprete this as following: the

Hello, I am working with rpart function but geting some error in prediction. the same code works fine with iris dataset. but applying other dataset it doesn't work. sample code is given for reference. > acc_model<-rpart(V1~V2+V3+V4+V5+V6+V7+V8, data=accEx.train) > plotcp(acc_model) >

I'm sory for my weak english. I need to analyze this subject : x1 x2 x3 x4 x5 x6 x7 x8 x9 x10 y 0 0 1 0 0 1 0 0 1 0 czarne 1 1 0 0 0 0 1 0 0 0 rude 0 0 1 0 0 1 1 0 0 0 braz 0 0 1 0 1 0 1 0 0 0 blond 1 0 0 0 0 1 0 0 0 1 rude 1 1 0 0 0 0 0 0 0 1 blond 0 0 1 1 0 0 0 0 1 0 czarne 1 0 0 1 0 0 1 0 0 0 blond 0 0 1 0 0 1 1 0 0 0 blond 1 0 0 0 0 1 1 0 0 0 czarne 0 0 1 0 0 1 0 0 0 1 czarne 1 0 1 0 0 0

Hello list, I'm having a problem with custom functions in rpart, and before I tear my hair out trying to fix it, I want to make sure it's actually a problem. It seems that, when you write custom functions for rpart (init, split and eval) then rpart no longer cross-validates the resulting tree to return errors. A simple test is to use the usersplits.R function to get a simple, custom

Dear r-devel, I am mutating rpart to do calculations on trees. I am trying to extract information from the tree. However, I got a seg. fault. This is the offending line in "rpmatrix.c": deltaI[0][0] = spl->improve; (Commenting it out cures the seg fault) I would like some advice on how to debug this. I have allocated memory with calloc and deltaI[0][0] should be

Should one expect minor numerical differences between 64bit and 32bit R on Windows? Hunting around the lists I've not been able to find a definitive answer yet. Seems plausible using different precision arithmetic, but waned to confirm from those who might know for sure. BACKGROUND A colleague was trying to replicate some modelling results (from a soon to be published book) using rpart, ada,

Hi there, I am interested in using R for machine learning (supervised classification). Currently, I have been investigating especially the rpart, tree, and randomForest package, and have achieved first results. are there any experiences, how the learned classificators could be used in e.g. C ? in other words, I want to "transfer" the learned predictor from R to C-code. for e.g. rpart,

Hi, >> I am interested in using R for machine learning (supervised classification). >> Currently, I have been investigating especially the rpart, tree, and randomForest package, and have >> achieved first results. >> >> are there any experiences, how the learned classificators could >> be used in e.g. C ? >> in other words, I want to

R-users E-mail: r-help@r-project.org Hi! R-users. http://finzi.psych.upenn.edu/R/library/mvpart/html/xpred.rpart.html says: data(car.test.frame) fit <- rpart(Mileage ~ Weight, car.test.frame) xmat <- xpred.rpart(fit) xerr <- (xmat - car.test.frame$Mileage)^2 apply(xerr, 2, sum) # cross-validated error estimate # approx same result as rel. error from printcp(fit) apply(xerr, 2,

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