similar to: dlda{supclust} 's output

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]]

Hi there, How to solve the conflicts as to the same object between two packages, for example, like margins in both randomForest and supclust? When both libraries are installed, supclust will complain "margins" defined in randomForest. I can only solve it by re-starting R, which is very inconvenient, any clever way? Thanks, Weiwei -- Weiwei Shi, Ph.D Research Scientist GeneGO, Inc.

Hi all, I downloaded a R package (supclust, not from CRAN) in my directory, then type: markov:/home/pingzhao> R CMD INSTALL supclust_1.1.tar.gz -l ~/lib but met the following errors * Installing *source* package 'supclust' ... ** libs /usr/local/lib/R/bin/SHLIB: make: not found ERROR: compilation failed for package 'supclust' Does it mean the R has not properly installed?

I'm going to implement AdaBoost algorithm in R. Just wanted to ensure that there is no implementation of any boosting algorithm in R... don't want to reinvent the wheel... -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-devel mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or

Hello, How can I do a cross validation in R? Thank You!

Hi, all, When running > AB.fit=adaboost(ylearn, xlearn, xtest, presel=0) I got the following error: Error in `[[<-.data.frame`(`*tmp*`, preds, value = c(4L, 6L, 6L, 6L, 3L, : replacement has 186 rows, data has 62 The data structure is attached below: [1] "ylearn" [1] 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 [40] 1 1 1 1 1 1 1 0

Hi! I'm using GLM, LDA and NaiveBayes for binomial classification. My training set is 70 rows long with 32 features, and my test set is 30 rows long with 32 features. Using Naive Bayes, I can train a model, and then predict the test set with it like so: ass4q1.dLDA = lda(ass4q1.trainSet[,1]~ass4q1.trainSet[,2:3]) table(predict(ass4q1.dNB, ass4q1.testSetDF[,2:3]), ass4q1.testSetDF[,1])

I want to speed up computations (involving matrices) by writing some C-code to be loaded. In the C-code, I need to invert matrices etc. As I've understood the "writing R extensions" doc, I can use use #include <R_ext/Linpack.h> in my .c-file and get access to linpack's facilities within my C-code. Is that correct? If so, can anyone point me to examples on how this is

Hi, I am a total newbie to R. I am using R (2.4.1) on Mac OS X 10.4.8 and trying to install some packages using GUI Packages & Data/Package Installer interface... Every time I get: trying URL 'http://umfragen.sowi.uni-mainz.de/CRAN/bin/macosx/universal/contrib/2.4/neural_1.4.1.tgz' Content type 'application/x-tar' length 18920 bytes opened URL

Hi all I am hoping this is just a minor problem, I am trying to implement a best subsets regression procedure on some ecological datasets using the regsubsets function in the leaps package. The dataset contains 43 predictor variables plus the response (logcount) all in a dataframe called environment. I am implementing it as follows: library(leaps)

On 5/2/07, r-help-request@stat.math.ethz.ch < r-help-request@stat.math.ethz.ch> wrote: > > Send R-help mailing list submissions to > r-help@stat.math.ethz.ch > > To subscribe or unsubscribe via the World Wide Web, visit > https://stat.ethz.ch/mailman/listinfo/r-help > or, via email, send a message with subject or body 'help' to >

Hi all, I'm using Pelora (supclust) package for supervised clustering of a microarray dataset. The original package does not delete the genes that are present in the earlier clusters for further cluster identification. This leaves us with mostly redundant clusters. I played around with the source code but couldn't get around it. Is there a way to fix it so that the genes already identified

I have run the following logistic regression model: options(contrasts=c("contr.treatment", "contr.poly")) m <- glm(wolf.cross ~ null.cross + feature, family = "binomial") where: wolf.cross = likelihood of wolves crossing a linear feature null.cross = proportion of random paths that crossed a linear feature feature = CATEGORY of linear feature with 5 levels:

Greetings! The Bioconductor core group would like to announce the 5th release of Bioconductor, version 1.4. There are many new packages as well as several major upgrades and fixes in older packages, and users are encouraged to upgrade existing tools and check out the new packages. Release 1.4 is intended to be operated with R version 1.9.x, which can be obtained at CRAN

The Bioconductor development team announces release 1.1 of the Bioconductor packages for the analysis of genomic data. Bioconductor is an open source bioinformatics software project based on R. Version 1.1 features: ===================== * All packages from the 1.0 release are included. All current bug fixes have been applied, and most have upgraded and provide enhanced functionality. *

The Bioconductor development team announces release 1.1 of the Bioconductor packages for the analysis of genomic data. Bioconductor is an open source bioinformatics software project based on R. Version 1.1 features: ===================== * All packages from the 1.0 release are included. All current bug fixes have been applied, and most have upgraded and provide enhanced functionality. *

The Bioconductor development team announces release 1.2 of the Bioconductor packages for the analysis of genomic data. Bioconductor is an open source bioinformatics software project based on the R language. Version 1.2 features: ===================== * All packages from the 1.1 release are included. All current bug fixes have been applied, and most have been upgraded and provide enhanced

The Bioconductor core group would like to announce the 1.3 release of the Bioconductor software. There are many new packages as well as several major upgrades and fixes in older packages, and users are encouraged to check them out. Release 1.3 is intended to be operated with R version 1.8.X, which can be obtained at CRAN (http://cran.r-project.org/) -- WHAT FEATURES DOES THIS RELEASE PROVIDE?

The Bioconductor core group would like to announce the 1.3 release of the Bioconductor software. There are many new packages as well as several major upgrades and fixes in older packages, and users are encouraged to check them out. Release 1.3 is intended to be operated with R version 1.8.X, which can be obtained at CRAN (http://cran.r-project.org/) -- WHAT FEATURES DOES THIS RELEASE PROVIDE?

Hi All Please see the Rprofile file which i have modified as follows and after that when I start R then I see that R says to me "TRUE" for all the packages implying that all loaded at once. But when i try to use commands as simple as help("lm"), it doesnt work nor any of the menu "Packages" is not working. Although the regression using lm ( Y ~ X ) is working