similar to: package mlbench updated

I'm discovering R (very impressive), and didn't find in the docs a simple method for replacing, in a data frame, missing values (NA) with the column's mean (or any other method for reconstructing missing values when needed). Thanks in advance for your help. -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

I've made a package from some benchmark datasets for use with R and uploaded it to CRAN. Here's the Index entry: mlbench-0.1.tar.gz: A collection of artificial and real-world machine learning benchmark problems, including, e.g., the boston housing data from the UCI repository. Written/packaged by Fritz Leisch <Friedrich.Leisch at ci.tuwien.ac.at> Original data sets from

I've made a package from some benchmark datasets for use with R and uploaded it to CRAN. Here's the Index entry: mlbench-0.1.tar.gz: A collection of artificial and real-world machine learning benchmark problems, including, e.g., the boston housing data from the UCI repository. Written/packaged by Fritz Leisch <Friedrich.Leisch at ci.tuwien.ac.at> Original data sets from

I've made a package from some benchmark datasets for use with R and uploaded it to CRAN. Here's the Index entry: mlbench-0.1.tar.gz: A collection of artificial and real-world machine learning benchmark problems, including, e.g., the boston housing data from the UCI repository. Written/packaged by Fritz Leisch <Friedrich.Leisch at ci.tuwien.ac.at> Original data sets from

I have a list of measurements taken at 1 second samples in a vector (y). All I want to do is generate a regression through them, and obtain the residuals in another vector. I am currently using the 'line' function from the eda package to do this (ie : z <- line(time,y) rsd <- residuals(z) ) but this method does not handle NA values in the data. I would like to try to use the lm

Hi all, I am doing bootstrap on a distance matrix, in which samples have been drawn with replacement. After that I do PCA on a resulted matrix, and these 2 steps are repeated 1000 times. pca(x) is a vector where I wanted to store all 1000 PCAs; and x is from 1 to 1000 SampleD is a new matrix after resampling; I am getting the following error message, which I don't understand: ....

Dear all: Subjects were measured two times (t1 and t2) on different variables (v1 ... vn). Between t1 and t2 there was an experimental manipulation. I computed two PCAs for time-points t1 and t2. Is it possible to combine both PCAs in order to get only one set of eigenvectors? Due to the experimental manipulation measurement values on time points t1 and t2 changed for each subject. Many

How does one rotate the loadings from a principal component analysis? Help on function prcomp() from package mva mentions rotation: Arguments retx a logical value indicating whether the rotated variables should be returned. Values rotation the matrix of variable loadings (i.e., a matrix whose olumns contain the eigenvectors). The function princomp returns this in the element

Hello all, if I have multiple imputed data sets, is there a command or function in R in any package you know of to combine those, I know one common MI approach is rubins rules, is there a way to do this using his rules or others? I know theres ways, like using Amelia from Gary King's website to create the imputed data sets, but how to make them into one or combine them for analysis.

Hi there, I am plotting relative warp scores (equivalent to pca scores) and I want to label (color code and shape) the points by group. I can't figure out how to do this beyond simple plotting. plot(RW1, RW2); Do I need to make vectors of each group and then plot them separately onto the same plot? How do I go about this? Thanks! -- View this message in context:

Hi all, I'm new to PCA in R, so this might be a basical thing, but I cannot find anything on the net about it. I need to make a PCA plot with two response variables (df$resp1 and df$resp2) against eight metabolites (df$met1, df$met2, ...) and I don't have a clue how to do... and I've only used the simplest PCAs before, like this: pcaObj=prcomp(t(df[idx, c(40:47)]))

Hi everyone, I'd like to project two pcas onto one device window. I plot my first PCA: biplot(prcomp(t(cerebdevmat)), var.axes=FALSE, cex=c(1,.1), pc.biplot=TRUE) Now I'd like to project the features of another PCA onto this graph. Any suggestions? I know this is easily done in MatLab but haven't figured it out in R. Thanks, Tanya [[alternative HTML version deleted]]

What R functionnalities are there to do missing values imputation (substantial proportion of missing data)? I would prefer to use maximum likelihood methods ; is the EM algorithm implemented? in which package? Thanks Anne ---------------------------------------------------- Anne Piotet Tel: +41 79 359 83 32 (mobile) Email: anne.piotet@m-td.com

Hello, I'm looking for a more descriptive manual/tutorial/paper for the pan package. The provided manual and example do not contain any useful hints how to specify a model with more than one variable and leaves several questions unanswered. This also applies to the referred paper "Schafer: Imputation of missing covariates under a multivariate linear mixed model." Can anyone

Dear R-users, Recently, I am facing some problems when converting mlbench data into matrix format. library(mlbench) data(BostonHousing) X<- BostonHousing[,1:13] y<-BostonHousing[,14] I want to convert X and y into matrix form. I am getting these obvious errors... > t(X)%*%y Error in t(X) %*% y : requires numeric/complex matrix/vector arguments > t(as.matrix(X))%*%(as.matrix(y))

Hi. I'm trying to plot a pair of intertwined spirals and an svm that separates them. I'm having some trouble. Here's what I tried. > library(mlbench) > library(e1071) Loading required package: class > raw <- mlbench.spirals(200,2) > spiral <- data.frame(class=as.factor(raw$classes), x=raw$x[,1], y=raw$x[,2]) > m <- svm(class~., data=spiral) > plot(m,

R-help, I am trying to perform a basic anlaysis of the BreastCancer data from "mlbench" using the svm() function in "e1071". I use the following code library("e1071") library("mlbench") data(BreastCancer) BC <- subset(BreastCancer, select=-Id) pairs(BC) model <- svm(Class ~ ., data=BC, cross=10) ## plot(model, BC, ) tobj <- tune.svm(Class ~ .,

Hola, quiero compartir con vosotros mi problema y la solución que me han planteado. Mi programa carga Outcomes.csv y Set-A.csv (descargados de http://garrickadenbuie.com/blog/2013/04/11/visualize-physionet-data-with-r/, apartado Getting Started --> the code and the data set) de unos 50MB entre los dos. Mi código era: # Transforma csv a data frame seta <- read.csv('Set-A.csv');

In testing the migration from courier-imap to dovecot I've discovered that the forward flag on messages isn't kept track of in a standard way. courier-imap seems to keep track of forwarded messages in courierimapkeywords/:list dovecot seems to add an 'a' flag to the filename. Unfortunately this 'a' flag information doesn't seem to be given out by dovecot. It's

Is it possible to have local users with mail in maildir:%h/.maildir and virutal users with mail in maildir:/home/exim/%u/.maildir I seem to have authentication working for both local users and LDAP users. But I'm getting this error trying to access a virtual users mail. Aug 17 08:12:08 hostname dovecot: IMAP(Firstname Lastname): maildir: