[R] problem with predict(mboost,...)

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

Re: [R] nu-SVM crashes in e1071

(...) > While you're sending your bug report to David, perhaps you can try the > SVM from kernlab. > > It relies on code from libsvm, too, but ... you never know. It can't > hurt to try. Hi Steve, thanks for that hint. I tried ksvm()-function bet get an error message: model <- ksvm(soil_unit~

Re: [R] nu-SVM crashes in e1071

> > I`m using SVMs for multi-class classification problems. Therefore I`m > using the svm() function in the package "e1071". > > If I use svm(...type="C-classification") everything works fine. But > if I want to use nu-SVM with svm(..., type="nu-classification", nu=0.5) > R crashes immediately. No

[R] nu-SVM crashes in e1071

Hello ! I`m using SVMs for multi-class classification problems. Therefore I`m using the svm() function in the package "e1071". If I use svm(...type="C-classification") everything works fine. But if I want to use nu-SVM with svm(..., type="nu-classification", nu=0.5) R crashes immediately. No er

[R] different randomForest performance for same data

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 data

[R] different model performance because of nlevels()???

Hello everybody, 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 variable

[R] creating lists in a list with loop

Hello ! I want to create a spatial stratified sampling scheme with the package spsurvey. To do this with the function "grts" in spsurvey, I need to create a list containing the specifications for each stratum. This specifications were stored in a named list, where the name for each stratum is t

[R] feature weighting in randomForest

Hello ! I´m using randomForest for classifacation problems. My dataset has 21.000 observations and 96 predictors. I know that some predictors of my dataset have more influence to classify my data than others. Therefore I would like to know if there is a way to weight my predictors. I know that

[R] "prob" in predict(randomForest)

Hi at all, maybe this question is quite simple for a statistician, but for me it is not. After reading a lot of mail in the R-help archive I`m still not quite sure I get it. When applying a randomForest to a new dataset with predict(randomForest) I have the option to get the output as probabil

[R] gbm for multi-class problems

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 m

Re: [R] dimnames in pkg "ipred"

attached a txt-file containing the str(traindat.bin) output from the data.frame, which I import via read.arff Cheers, TIM -Ursprüngliche Nachricht- Von: Uwe Ligges [mailto:lig...@statistik.tu-dortmund.de] Gesendet: Friday, January 23, 2009 11:03 AM An: Häring, Tim (LWF) Betreff: Re: AW: [R

Re: [R] dimnames in pkg "ipred"

, January 22, 2009 6:49 PM An: Häring, Tim (LWF) Cc: r-help@r-project.org Betreff: Re: [R] dimnames in pkg "ipred" Häring, Tim (LWF) wrote: > Hello List, > > > > I`m trying to make prediction using a bagged tree with the package ipred. I > tried to follow the man

[R] dimnames in pkg "ipred"

Hello List, I`m trying to make prediction using a bagged tree with the package ipred. I tried to follow the manual but I`m getting an error message. Also browsing through the list-archive I didn`t find any hint. Maybe someone can help me? selbag <- bagging(SOIL_UNIT ~., data=traindat.bi

[R] problems with extractPrediction in package caret

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 b

[R] Question about the RWEKA package

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