similar to: Shared nearest neighbor (SNN) clustering algorithm implementation?

Several of the methods I use for analyzing large data sets, such as WinGamma: determining the level of noise in data Relief-F: estimating the influence of variables depend on finding the k nearest neighbors of a point in a data frame or matrix efficiently. (For large data sets it is not feasible to compute the 'dist' matrix anyway.) Seeing the proposed solution to "[R] distance

https://bugs.freedesktop.org/show_bug.cgi?id=94817 Bug ID: 94817 Summary: Nearest neighbor scaling? Product: xorg Version: unspecified Hardware: Other OS: All Status: NEW Severity: enhancement Priority: medium Component: Driver/nouveau Assignee: nouveau at

Is fast nearest-neighbor functionality available in R? I was thinking of something along the lines of what's currently in S+SPATIALSTATS. Thanks for any information anyone might have on this. - MZ

Dear R users, Is there anyone who is aware of a R or S package that has Discriminant Adaptive Nearest Neighbor (DANN) classification by Hastie and Tibshirani? I have used the search services in R website but no luck. Thanks in advance! Jonathan -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

Hello everyone, Is there anyone who is aware of any R package that has Discriminant Adaptive Nearest Neighbor (DANN) classification by Hastie and Tibshirani? Thanks in advance! Tracy [[alternative HTML version deleted]]

I've written the function below to simulate the mean 1st through nth nearest neighbor distances for a random spatial pattern using the functions nndist() and runifpoint() from spatsat. It works, but runs relatively slowly - would appreciate suggestions on how to speed up this function. Thanks. --Dale library(spatstat) sim.nth.mdist <- function(nth,nsim) { D <- matrix(ncol=nth,

Hi there fellow R-users, Does anyone know if there is a package for k nearest neighbours prediction as opposed to classification? I have found the package knncat but can't see a way to adjust it to predict a continuous variable. Any help would be great, Regards Wayne Jones KSS Ltd Seventh Floor St James's Buildings 79 Oxford Street Manchester M1 6SS England Company

I was wondering if there is a way in R to find k nearest neighbors of various orders, say order 2, 3, or 4. In otherwords neighbors of neighbors of neighbors. You get the idea. I know that I can use knearneigh(matrix.data, k) but this only gives me the k nearest neighbors and not of a particular order. Thanks in advance. -- View this message in context:

Is there an implementation of a reasonable k-nearest neighbor finder already in one of the packages? -- +---------------------------------------------------------------------------+ | Robert Gentleman phone : (617) 632-5250 | | Associate Professor fax: (617) 632-2444 | | Department of Biostatistics office: not yet

I'm trying to do the following: For each ordered pair of a data frame (D1) containing longitudes and latitudes and unique point IDs, calculate the distance to every point in another data frame (D2) also containing longitudes, latitudes and point IDs, and return to a new variable in D1 the point ID of the nearest element of D2. Dramatis personae (mostly self-explanatory): D1$long

hi, I have a dataset (the netflix dataset) which is basically ~18k columns and well variable number of rows but let's assume 25 thousand for now. The dataset is very sparse. I was wondering how to do kmeans/nearest neighbors or kernel density estimation on it. I tired using the spMatrix function in "Matrix" package. I think I'm able to create the matrix but as soon as I pass

Dear All, I cannot find a solution to the following problem although I imagine that it is a classic, hence my email. I have a vector V of X values comprised between 1 and N. I would like to get random samples of X values also comprised between 1 and N, but the important point is: * I would like to keep the same distribution of distances between the X values * For example let's say N=10 and

Dear Help List, My name is Matt Oliver. I have been using R for about a year and find it very helpful. However, I have a need for a function that I cannot find. I am not very good at programming so I thought I would ask the group. I have an irregular grid of data (x = Longitude, y = Latitude). Each pair of my x,y has a categorical value. Obviously linear or any other numerically based

Dear R users, I?m please to announce the available on CRAN of new package largeVis.(*) largeVis offers three major features: - A fast implementation of the LargeVis algorithm. LargeVis is for visualizing high-dimensional datasets, similar to (and of similar quality to) t-SNE. But, LargeVis runs in O(n) time, which makes it feasible to use on datasets with millions of rows and thousands of

Dear R users, I?m please to announce the available on CRAN of new package largeVis.(*) largeVis offers three major features: - A fast implementation of the LargeVis algorithm. LargeVis is for visualizing high-dimensional datasets, similar to (and of similar quality to) t-SNE. But, LargeVis runs in O(n) time, which makes it feasible to use on datasets with millions of rows and thousands of

Dear Rs: BY having the following code: candidates<-expand.grid(e=c("nearest-neighbor","exaustive"), d=c(70,75,80,85,90,92,94,96,98,99), n=c(20,25,30,35,40)) results in : e d n 1 nearest-neighbor 70 20 2 exaustive 70 20 3 nearest-neighbor 75 20 4 exaustive 75 20 ................ 90 exaustive 90 40 91 nearest-neighbor 92 40 92 exaustive 92 40 93 nearest-neighbor 94 40 94

Robust Covariance Estimation Software via Nearest Neighbor Variance Estimation (NNVE) Software to carry out robust covariance estimation by Nearest Neighbor Variance Estimation (NNVE) [Wang and Raftery (2002, J. Amer. Statist. Ass.)] is now available for R and Splus. In the simulation studies published in JASA, this had mean squared error at least 100 times smaller than that of other leading

Robust Covariance Estimation Software via Nearest Neighbor Variance Estimation (NNVE) Software to carry out robust covariance estimation by Nearest Neighbor Variance Estimation (NNVE) [Wang and Raftery (2002, J. Amer. Statist. Ass.)] is now available for R and Splus. In the simulation studies published in JASA, this had mean squared error at least 100 times smaller than that of other leading

Hi R people, i'm looking for the Reciprocal Nearest Neighbour algorithm applied to Ward clustering; I know that it is explained in details in the following book: Downs, G. M.; Willett, P. In Advanced Computer-Assisted Techniques in Drug Discovery; van de Waterbeemd, H., Ed.; VCH: Weinheim, 1994; Vol. 3. but cannot order copies it without knowing the pages involved; could someone

Anyobody knows if functions neighbor.grid and spatial.weights (from module spatial) have any 'equivalents' in R ? Thanks. JA -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the