similar to: name conflicts

When I sink the output of an RWeka model to a text file, the output file appears empty: library(RWeka) model = LogitBoost(Species~.,data=iris) print(model) sink("output.txt") print(model) #file output.txt is created, but it is blank sink() Am I doing anything wrong? [[alternative HTML version deleted]]

Working on the caret package has exposed me to the wide variety of approaches that different authors have taken to creating predictive modeling functions (aka machine learning)(aka pattern recognition). I suspect that many package authors are neophyte R users and are stumbling through the process of writing their first R package (or R code). As such, they may not have been exposed to some of the

I was trying to produced bagged importance estimates of attributes in earth using the caret package with the following commands:   fit2 <- bagEarth(loyalty ~ ., data=model1, B = 10)   bagImpGCV <- varImp(fit2,value="gcv") My bootstrap estimates are produced however the second command "varImp" produces the following error:    Error in UseMethod("varImp") : no

Hello, does any one know how to interpret this output in R? > Classification with logitboost > fit <- logitboost(xlearn, ylearn, xtest, presel=50, mfinal=20) > summarize(fit, ytest) Minimal mcr: 0 achieved after 6 boosting step(s) Fixed mcr: 0 achieved after 20 boosting step(s) What is "mcr" mean? Thanks [[alternative HTML version deleted]]

I've had a lot of requests for additions to the reproducible research task view that fall into a grey area (to me at least). For example, roxygen2 is a tool that broadly enable reproducibility but I see it more as a tool for better programming. I'm about to check in a new version of the task view that includes packrat and checkpoint, as they seem closer to reproducible research, but also

The CRAN policy page (https://cran.r-project.org/web/packages/policies.html) implies that there is a formal procedure for orphaning a package but none is mentioned in the Extensions manual (https://cran.r-project.org/doc/manuals/r-devel/R-exts.html). This page (https://cran.r-project.org/src/contrib/Orphaned/README) implies that one would simply resubmit the package to CRAN with the text

Hello, I was wondering what would be the easiest way to append weights to a dataset in RWeka. Ideally, I'd like to have something like: m <- LogitBoost(Species ~ ., data=iris, weights = myweights) But that, as far as I understand, it is not implemented and I'd need to use a workaround. I know that when programming Weka in Java it is possible to assign weights to instances using

I had installed de "gplots" package and then I loaded the library but the package did not work. I recieved a message like this: > install.packages("gplots", dependencies = TRUE) Installing package(s) into ‘/home/fpiston/R/x86_64-pc-linux-gnu-library/2.14’ (as ‘lib’ is unspecified) --- Please select a CRAN mirror for use in this session --- Loading Tcl/Tk interface ... done

Dear all, i searched for some classification methods and I have no glue if i took the right once. My problem: I have a matrix with 17000 rows and 33 colums (genes and patients). The patients are grouped into 3 diseases. No I want to classify the patients and for sure i want to know which rows are more helpful for the classification than others. I tried SVM and random forest. Do you think this

Everyone, I'm working with scatter plots with different colored symbols (via lattice). I'm currently using these colors for points and lines: col1 <- c(rgb(1, 0, 0), rgb(0, 0, 1), rgb(0, 1, 0), rgb(0.55482458, 0.40350876, 0.04166666), rgb(0, 0, 0)) plot(seq(along = col1), pch = 16, col = col1, cex = 1.5) I'm also using these with transparency (alpha

Hi, I downloaded RWeka successfully. (At least I do not see, where I could have made a mistake.) Then I tried to load it by the library-command. To my surprise this did not work. Result: library(RWeka) Fehler in .jinit(c(system.file("jar", "weka.jar", package = "RWeka"), system.file("jar", : Cannot create Java Virtual Machine Fehler: .onLoad in

Hi, I am having problems passing arguments to method="gbm" using the train() function. I would like to train gbm using the laplace distribution or the quantile distribution. here is the code I used and the error: gbm.test <- train(x.enet, y.matrix[,7], method="gbm", distribution=list(name="quantile",alpha=0.5), verbose=FALSE,

Hi, I have a question about using RWeka Clusterers.If you could supply answer or insight, I would really appreciate it. When I run a simple code which uses a clusterer from RWeka I get an error. the sample codes and errors are mentioned below Code: library(RWeka) Cobweb(iris[,-5],control=NULL) Error: Error in names(class_ids) <- nms : 'names' attribute [150] must be the same

Hi, I tried to install the caTools package manually from the main R Project website and I get the following error message when typing library('caTools') Error in library("caTools") : 'caTools' is not a valid package -- installed < 2.0.0? What am I doing wrong? Also, why is this package not available in the list of packages for direct installation from the R

Hi, I suddenly started getting strange errors while working on my caTools package: >RCMD install C:/programs/R/rw2011/src/library/caTools ...... preparing package caTools for lazy loading Error in file(file, "r", encoding = encoding) : all connections are in use Execution halted make: *** [lazyload] Error 1 *** Installation of caTools failed *** I searched

Dear R-users, I am running R 2.10.1 under Windows XP Professional. Moreover, I run Java 5.0 and the RWeka package 0.4-1 and rJava 0.8-4. are successfully installed. I get two error messages while loading both packages. library(RWeka) Error in get(Info[i, 1], envir = env) : internal error -3 in R_decompress1 Error: package/namespace load failed for 'RWeka' 2:

Dear list, I am using R.2.11.1 version on a PC. I downloaded successfully gplots_2.8.0 but I could not find where to download caTools > library("gplots") Loading required package: caTools Error: package 'caTools' could not be loaded In addition: Warning message: In library(pkg, character.only = TRUE, logical.return = TRUE, lib.loc = lib.loc) : there is no package called

Dear All, I'd like to use Weka functions that are not implemented (do not have interface) in RWeka, like the Remove function and others in the future! The .java() functionality is for that purpose but I haven't seen any example with Weka functions. Could anyone give me hand in how to do it? For instace if I want to use the weka.filters.unsupervised.attribute.Remove? 1. in the R console,

Howdy Gurus again Thanks to Tony.Breyal, I was able to writing the following script for analyzing a text document. But I got an error with "tm' package. I don't why I got the error from the R script below. I think I followed proccess of R tm manual. I use R v2.8.1. and tm_0.3-3.zip under Win XP. Thanks in advance, Kum Hwang > # setting directory > my.path

Dear All, I am far from being a guru about parallel programming. Most of the time, I rely or randomForest for data mining large datasets. I would like to give a try also to the gradient boosted methods in GBM, but I have a need for parallelization. I normally rely on gbm.fit for speed reasons, and I usually call it this way gbm_model <- gbm.fit(trainRF,prices_train, offset = NULL, misc =