similar to: dimnames in pkg "ipred"

Dear List, I´m trying to implement the functionalities from WEKA into my modeling project in R through the RWeka package. In this context I have a slightly special question about the filters implemented in WEKA. I want to convert nominal attributes with k values into k binary attributes through the NominalToBinary filter ("weka.filters.supervised.attribute.NominalToBinary"). But

Hi list, I´m working on a predictive modeling task using the caret package. I found the best model parameters using the train() and trainControl() command. Now I want to evaluate my model and make predictions on a test dataset. I tried to follow the instructions in the manual and the vignettes but unfortunately I´m getting an error message I can`t figure out. Here is my code: rfControl <-

Hello, I came across a problem when building a randomForest model. Maybe someone can help me. I have a training- and a testdataset with a discrete response and ten predictors (numeric and factor variables). The two datasets are similar in terms of number of predictor, name of variables and datatype of variables (factor, numeric) except that only one predictor has got 20 levels in the training

Hello, I want to draw 3D cylinder objects in R. Given is the length and the diameter of the cylinder. Has anybody an example? Thank you very much! Best regards -- ---------------------- Dr. Hans-Joachim Klemmt Forstoberrat Organisationsprogrammierer IHK Bayerische Landesanstalt f?r Wald und Forstwirtschaft zugewiesen an Lehrstuhl f?r Waldwachstumskunde Technische Universit?t M?nchen

I wanted to report this issue here so others may not find themselves alone and as the author is apparently active on the list. I havent done an exhaustive test by any means, cause I dont have time. But here's a small example. Apparently the "ns" argument is the one that is killing it. I've gotten several different segfault messages, the only other one I remember said "out

The data frame is lwf that records the survival of bushes over an 8 year period. Years are called bouts. Dead bushes are recorded as zeros, and live bushes as "1." str(lwf) 'data.frame': 638 obs. of 9 variables: $ bushno: int 1 2 3 4 5 6 7 8 9 10 ... $ bout1 : int 0 1 0 1 1 1 0 1 0 1 ... $ bout2 : int 0 1 0 0 0 0 0 0 0 1 ... $ bout3 : int 0 1 0 0 0 0 0 0 0 1 ... $

Dear List, I´m working on a classification problem. My response has 60 levels. I`m very interested in boosted trees like AdaBoost or gradient boosting machine as implemented in the package "gbm". Unfortunately gbm is only applicable for 2-class problems. Is anybody out there who can help me? Is there a way to use gbm() for multi-class problems? Maybe there is a way to transform my

Hi, I use a mboost model to predict my dependent variable on new data. I get the following warning message: In bs(mf[[i]], knots = args$knots[[i]]$knots, degree = args$degree, : some 'x' values beyond boundary knots may cause ill-conditioned bases The new predicted values are partly negative although the variable in the training data ranges from 3 to 8 on a numeric scale. In order 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

Dear all, can anybody help me with the program below? The function predict.lda seems to be defined but cannot be used by errortest. The R version is 1.7.1 Thanks in advance, Stefan ---------------- library("MASS"); library("ipred"); data(iris3); tr <- sample(1:50, 25); train <- rbind(iris3[tr,,1], iris3[tr,,2], iris3[tr,,3]); test <- rbind(iris3[-tr,,1],

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",

The package ipred is uploaded to CRAN. The main focus of the package is the calculation of improved predictors in classification tasks. Misclassification error can be improved by bootstrap aggregated classification trees and/or the framework of indirect classification. Furthermore, a unified interface for the estimation of misclassification error completes the features of ipred. We try to make

The package ipred is uploaded to CRAN. The main focus of the package is the calculation of improved predictors in classification tasks. Misclassification error can be improved by bootstrap aggregated classification trees and/or the framework of indirect classification. Furthermore, a unified interface for the estimation of misclassification error completes the features of ipred. We try to make

Hi List, Im new to postfix-dovecot and im mystified by the following results in ubuntu 10.04lts :~$ dovecot -n # 1.2.9: /etc/dovecot/dovecot.conf Error: ssl_key_file: Can't use /etc/ssl/private/ssl-mail.key: Permission denied Fatal: Invalid configuration in /etc/dovecot/dovecot.conf ~$ sudo ls -dl /etc/ssl/private/ssl-mail.key lrwxrwxrwx 1 root root 38 2013-11-27 08:35

Last week Giovanni Parrinello posted a message asking why various packages were loaded when he loaded an .Rdata file. Brian Ripley replied saying he thought it was because the saved workspace contained a reference to the namespace of ipred. (Correspondence copied below). This begs the question: how did the reference to the namespace of ipred come to be in the .Rdata file? Brian did say it is

Dear R users, I have been using the rpart procedure to predict the occurrence of depression in a large data file. Since the prevalence is very low (5%), I have been using classification trees with a loss matrix that penalized false negatives more than false positives. I have become interesested in bagging these (successful!) classification trees, and have been using the ipred package for

Hello! I'm Taeho, a graduate student in South Korea. In order to get .632+ bootstrap error using random forest, I have tried to use 'ipred' package; more specifically the function 'errorest' has been used. Following the guidelines, I made a simple command line like below: error<-errorest(class ~ ., data=data, model=randomForest, estimator = "632plus")$err

Hi, I'm trying to find information about rsurv "Simulating Survival data" in the IPred package, without luck this far. In the description of this function we are asked to consult Hothorn et al. (2003) for the details. This paper is not in the reference list. Should it be same authors (2004)? In that case I will try my library, in any other case could someone please give me

Hello, can me please help anbody how it is possible unlist a "rpart.object.list" i.e. from bagging(ipred) to plot this "unique" several rpart.objects . ..i make attempts with unlist, get really atomic elements, but need only the different tree's ! Thanks for advance & regards,Christian -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-

Apologies - I was not trying to correct you Brian, but to explore how the situation could arise. I'm sure you had a good idea why the namespace (or a reference to it) had been saved, but this was not clear to me and I thought, possibly not to others either. Thanks for putting me right over parent environments vs. enclosures - again I was not trying to correct you with the point I made there,