Displaying 7 results from an estimated 7 matches for "wordspac".
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wordspace
2017 Jun 18
2
dist function in R is very slow
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);?...
2010 Jan 21
2
"stack imbalance in ..." when loading a workspace
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...
2012 Jun 16
1
Efficient distance calculation on big matrix
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
2017 Jun 18
0
dist function in R is very slow
...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...
2013 Oct 03
1
Random Projection
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,
2017 Jun 17
1
dist function in R is very slow
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,
2009 Aug 21
0
Wine release 1.1.28
...nt IHTMLLocation get_href.
msxml3: Support loading windows file paths.
mshtml: Implement IHTMLCurrentStyle_get_visibility.
mshtml: Implement IHTMLStyle get/put borderLeftWidth.
mshtml: Implement HTMLCurrentStyle_get_borderLeftWidth.
mshtml: Implement IHTMLStyle get/put wordSpacing.
Andrew Eikum (14):
gdiplus: Create utility function get_graphics_bounds.
gdiplus: Implement GdipGetVisibleClipBounds.
gdiplus/tests: Add tests for GdipGetVisibleClipBounds.
comctl32: Don't pass unrelated control to UnChanged.
comctl32: Correctly assign focus a...