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What you've shown us looks inconsistent: The data frame you show has variables X1 through X5 and `class'. If this is a data frame named `data', why do you call tree() with the formula V1 ~ X1? Where is V1? `data' is the name of a built-in R function. Try using some other name for the data frame. Also, give us the output of traceback() after the error occur. That should help.

hi, I am encoutering a very little problem that seemed to be so easy to solve.... I need to divide the array > A<-c(1:200) into two subsets at random. Therefore I use the function "sample" in R: > S<-sample(A,100) for a random sample of size 100. Then I need the values in A that are not selected in S to be put in another array, there is my problem! Is there anyway to do

Hi I saw your problem on the Samba Mailing list <Hi, we are encoutering some curious problems in our office network: Print-jobs from windows 2k/xp clients are only printed once, although the user wanted the same document to be printed several times. Does anyone have an idea? Has anyone had the same problem?> We are running HP LaserJet 4200ns on the same network and are having the

Hi, I had successfully set up dovecot-1.0-test62 + ldap pass/user db, but now I'm encoutering a SIGSEV problem with a similar set up of a brand new dovecot-1.0-test65 installation. The auth process is killed by a SIGSEV as reported in the error log file : dovecot: Mar 30 17:06:59 Error: child 28291 (auth) killed with signal 11 To be precise, the problem occurs in the

Dear R users, I am encoutering the following problem: I have a dataset with a 'unique_id' and different 'visit_date' (formatted as.Date, "%d/%m/%Y") per unique_id. I would like to create a new variable with the most recent date of visit per unique_id as shown below. unique_id visit_date last_visit_date 1 01/06/2010 01/06/2011 1 01/01/2011 01/06/2011 1

Hi there. I m really impressed by the icecast tools and have been spending some times playing with it. Friends of mine use the server but as they are not really at ease with telneting for administrative purpose i had a try creating some php pages that will act as an administrative tools for icecast. Unfortunateley i didn t found any library that may help me communicate with the icecast server.

Full_Name: Merlise Clyde Version: 2.8.1 OS: MAC OS X 10.4.1 Submission from: (NULL) (24.199.155.61) I am running R under X11 on the MAC OS X 10.4.11 and have been having problems with X11 graphics since upgrading to 2.8.+ > plot(1:10) Error in X11(d$display, d$width, d$height, d$pointsize, d$gamma, d$colortype, : unable to start device X11cairo In addition: Warning messages: 1: In

Dear R-users, I'm encoutering some problems with the qcc()-function. When there are more than 25 replicates per "sample" the estimate for the standard deviation becomes NA, implying that nothing is plotted (error message: "Error in plot.window(...) : need finite 'ylim' values") On the forum I found a way to work around the error message, but this does not

fit1<-rq(formula=op~inp1+inp2+inp3+inp4+inp5+inp6+inp7+inp8+inp9,tau=0.15,data=wbc) fit2<-rq(formula=op~inp1+inp2+inp3+inp4+inp5+inp6+inp7+inp8+inp9,tau=0.5,data=wbc) fit3<-rq(formula=op~inp1+inp2+inp3+inp4+inp5+inp6+inp7+inp8+inp9,tau=0.15,data=wbc) fit4<-rq(formula=op~inp1+inp2+inp3+inp4+inp5+inp6+inp7+inp8+inp9,tau=0.15,data=wbc)

hi, I would like to subsample the array c(1:200) at random into ten subsamples v1,v2,...,v10. I tried with to go progressively like this: > x<-c(1:200) > v1<-sample(x,20) > y<-x[-v1] > v2<-sample(y,20) and then I want to do: >x<-y[-v2] Error: subscript out of bounds.

Hi, I'm trying to melt() some data for subsequent cast()ing and am encoutering errors. The overall process requires a couple of casts()s and melt()s. ########Start Session 1########## ## I have the data in a (fully) melted format and can cast it fine... > norm1[1:10,] Pool SNP Sample.Name variable value 1 1 rs1045485 CA0092 Height.1 0.003488853 2 1 rs1045485

Dear all, Does anybody can explain this: different results got when all the same parameters are used in the errorest() in library ipred, as the following? errorest(Species ~ ., data=iris, model=randomForest, estimator = "cv", est.para=control.errorest(k=3), mtry=2)$err [1] 0.03333333 > errorest(Species ~ ., data=iris, model=randomForest, estimator = "cv",

https://bugzilla.samba.org/show_bug.cgi?id=2208 wayned@samba.org changed: What |Removed |Added ---------------------------------------------------------------------------- Severity|major |normal Status|NEW |ASSIGNED Summary|rsync failed at random file |cygwin version of rsync

Is it possible to make multiple plots i.e. to represent more than one function on the same figure? Thank you Email: botti23@libero.it [[alternative HTML version deleted]]

Here is a snippet to show what i'm trying to do. library(randomForest) library(ROCR) library(caret) data(iris) iris <- iris[(iris$Species != "setosa"),] fit <- randomForest(factor(Species) ~ ., data=iris, ntree=50) train.predict <- predict(fit,iris,type="prob")[,2]

hi, I am trying to grow a classification tree on some data, but I have a little problem. In order to do so I have to use a function like "tree" in R and on the internet help(tree) I get the following: "The left-hand-side (response) should be either a numerical vector when a regression tree will be fitted or a factor, when a classification tree is produced" I would like to

Dear List, I have a question regarding "ipred" package. Under 10-fold cv, for different knn ( = 1,3,...25), I am getting same misclassification errors: ############################################# library(ipred) data(iris) cv.k = 10 ## 10-fold cross-validation bwpredict.knn <- function(object, newdata) predict.ipredknn(object, newdata, type="class") for (i in

Greetings, I have been exploring the use of the caret package to conduct some plsda modeling. Previously, I have come across methods that result in a R2 and Q2 for the model. Using the 'iris' data set, I wanted to see if I could accomplish this with the caret package. I use the following code: library(caret) data(iris) #needed to convert to numeric in order to do regression #I

hi! this is a question about lda (MASS) in R on a particular dataset. I'm not a specialist about any of this but: First with the well-known "iris" dataset, I tried using lda to discriminate versicolor from the other to classes and I got approx. 70% of accuracy testing on train set. In iris, versicolor stands "between" the 2 other so one can expect lda not to perform well

I've been using the pcaMethods to develop a scores matrix ======================================= data(iris) pcIr <- pca(iris[,1:4], method="nipals", nPcs=3, cv="q2") test <- scores(pcIr) ======================================== What I'm looking to do is to use lattice's barchart to plot the scores something like below, but expanded to all the scores