search for: wordspace

Hi Stefan, Thank you very much for pointing me to the wordspace package. It does the job a bit faster than my C code but is 100 times more convenient. By the way, since the tcrossprod function in the Matrix package is so fast, the Euclidean distance can be computed very fast: euc_dist <- function(m) {mtm <- Matrix::tcrossprod(m); sq <- rowSums(m*m);? s...

Hi all, I just failed in loading a saved wordspace (13MB of size), and received these errors: Warning: stack imbalance in 'missing', 52 then 51 Warning: stack imbalance in 'if', 50 then 53 Warning: stack imbalance in 'as.environment', 57 then 59 Warning: stack imbalance in 'ls', 54 then 53 Warning: stack imbalance...

Hi All, I'm working on analyzing a large data set, lets asume that dim(Data)=c(1000,8700). I want to calculate the canberra distance between the columns of this matrix, and using a toy example ('test' is a matrix filled with random numbers 0-1): > system.time(d<-as.matrix(dist(t(test), method = "canberra", diag = FALSE, upper = FALSE, p = 2))) user system

...on in the Matrix package is so fast, the Euclidean distance can be computed very fast: Indeed. > euc_dist <- function(m) {mtm <- Matrix::tcrossprod(m); sq <- rowSums(m*m); sqrt(outer(sq,sq,"+") - 2*mtm)} There are two reasons why I didn't use this optimization in "wordspace": 1) It can be inaccurate for small distances between vectors of large Euclidean length because of loss of significance in the subtraction step. This is not just a theoretical concern ? I've seen data sets were this became a real problem. 2) It incurs substantial memory overhead for a l...

Hello: I was wondering, has anyone has encountered an R package that performs random projection/random mapping? RP is a procedure that is akin to Principal Components Analysis in that it accomplishes dimensionality reduction, but is far more computationally efficient. I have been searching for some time, but haven't seen anything on CRAN-r yet. David Monaghan Sociology Ph.D. Candidate,

Dear R developers, I am visualising high dimensional genomic data and for this purpose I need to compute pairwise distances between many points in a high-dimensional space (say I have a matrix of 5,000 rows and 20,000 columns, so the result is a 5,000x5,000 matrix or it's upper diagonal).Computing such thing in R takes many hours (I am doing this on a Linux server with more than 100 GB of RAM,

The Wine development release 1.1.28 is now available. What's new in this release (see below for details): - Support for IRDA protocol. - Faster initial wineprefix creation. - Axis remapping with evdev joysticks. - More image formats in WindowsCodecs. - Various bug fixes. The source is available from the following locations: