similar to: problems with extractPrediction in package caret

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.bin, coob=TRUE) Error in dimnames(X) <- list(dn[[1L]], unlist(collabs, use.names = FALSE)) :

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 all I am using the caret package and having difficulty in obtaining the results using regression, I used the glmnet to model and trying to get the coefficients and the model parameters I am trying to use the extractPrediction to obtain a confusion matrix and it seems to be giving me errors. x<-read.csv("x.csv", header=TRUE); y<-read.csv("y.csv", header=TRUE);

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 ... $

I want to use the caret package to train linear models. I want to compare these models when using different degrees (aka degrees of interaction). This is possible for the 'earth' method (using the '.degree' parameter) but I found no possibility of customizing the degree for the 'lm' method. This might be due to the fact that the basic 'lm' function does not support

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

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

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

I am used to packages like e1071 where you have a tune step and then pass your tunings to train. It seems with caret, tuning and training are both handled by train. I am using train and trainControl to find my hyper parameters like so: MyTrainControl=trainControl( method = "cv", number=5, returnResamp = "all", classProbs = TRUE ) rbfSVM <- train(label~., 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 datatype of variables (factor, numeric) except that only one predictor has got 20 levels in the training

I have a function: myplot <- function (X) { d <- plotCounts(dds2, gene=X, intgroup="condition", returnData=TRUE) png(paste("img/", X, ".png", sep="")) ggplot(d, aes(x=condition, y=count, color=condition)) + geom_point(position=position_jitter(w=0.1,h=0)) + scale_y_log10(breaks=c(25,100,400)) + ggtitle(X) +

I don't really understand. I mean, I understand the solution is print(ggplot(...)). But why is that required in a function and not at the console? Shouldn't I be able to rely on what I do at the console working in a script? Is this inconsistent behavior by design? On Thu, Nov 2, 2017 at 11:54 AM, David Winsemius <dwinsemius at comcast.net> wrote: > >> On Nov 2, 2017,

> On Nov 2, 2017, at 9:27 AM, Ed Siefker <ebs15242 at gmail.com> wrote: > > I have a function: > > myplot <- function (X) { > d <- plotCounts(dds2, gene=X, intgroup="condition", returnData=TRUE) > png(paste("img/", X, ".png", sep="")) > ggplot(d, aes(x=condition, y=count, color=condition)) + >

Dear all, I am using the "caret" Package for predictors selection with a randomForest model. The following is the train function: rfFit<- train(x=trainRatios, y=trainClass, method="rf", importance = TRUE, do.trace = 100, keep.inbag = TRUE, tuneGrid = grid, trControl=bootControl, scale = TRUE, metric = "ROC") I wanted to use ROC as the metric for variable

Dear developers, I have jutst started working with caret and all the nice features it offers. But I just encountered a problem: I am working with a dataset that include 4 predictor variables in Descr and a two-category outcome in Categ (codified as a factor). Everything was working fine I got the results, confussion matrix etc. BUT for obtaining the AUC and predicted probabilities I had to add

Hi, I am trying to construct a svmpoly model using the "caret" package (please see code below). Using the same data, without changing any setting, I am just changing the seed value. Sometimes it constructs the model successfully, and sometimes I get an ?Error in indexes[[j]] : subscript out of bounds?. For example when I set seed to 357 following code produced result only for 8

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

I'm using caret to assess classifier performance (and it's great!). However, I've found that my results differ between R2.* and R3.* - reported accuracies are reduced dramatically. I suspect that a code change to kernlab ksvm may be responsible (see version 5.16-24 here: http://cran.r-project.org/web/packages/caret/news.html). I get very different results between caret_5.15-61 +

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 On Thu, 6 Feb 2014, Phil wrote: > Im new to postfix-dovecot and Unix/Linux, too? > 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 >

This e-mail - summarizes some of the responses/suggestions to using R for 13 year olds from my query on this list - discusses some additional investigation I did - the approach I am currently using (which will likely incorporate your suggestions for R) SUGGESTIONS - find relationship between monthly heating bills and temperature. For data see