[R] K-means results understanding!!!

Dear members. I am having problems to understand the kmeans- results in R. I am applying kmeans-algorithms to my big data file, and it is producing the results of the clusters. Q1) Does anybody knows how to find out in which cluster (I have fixed numberofclusters = 5 ) which data have been

Re: [R] K-means results understanding!!!

:25 AM To: r-help@r-project.org Subject: [R] K-means results understanding!!! Dear members. I am having problems to understand the kmeans- results in R. I am applying kmeans-algorithms to my big data file, and it is producing the results of the clusters. Q1) Does anybody knows how to find out

Re: [R] K-means results understanding!!!

Hi, Thanks for reply but I already read the help page I am new in R and did not understand the output description of kmeans -function. That is why I wanted to ask some experts in the group. My point is that I do not understand which data are combined in the specific cluster? I tried the

Re: [R] K-Means clustering Algorithm

Message- From: r-help-boun...@r-project.org [mailto:r-help-bounces@r- project.org] On Behalf Of olemissrebs1123 Sent: Tuesday, August 28, 2012 3:16 PM To: r-help@r-project.org Subject: [R] K-Means clustering Algorithm I was wondering if there was an R equivalent to the two phased approach

[R] K-Means clustering Algorithm

I was wondering if there was an R equivalent to the two phased approach that MATLAB uses in performing the Kmeans algorithm. If not is there away that I can determine if the kmeans in R and the kmeans in MATLAB are essentially giving me the same clustering information within a small amount of

Re: [R] k-means++

Ferebee Tunno ferebee.tunno at mathstat.astate.edu writes: Hi everyone - I know that R is capable of clustering using the k-means algorithm, but can R do k-means++ clustering as well? k-means++ is a routine to suggest center points before the classical k-means is called. The following

[R] k-means++

Hi everyone - I know that R is capable of clustering using the k-means algorithm, but can R do k-means++ clustering as well? Thanks, -- Dr. Ferebee Tunno Assistant Professor Department of Mathematics and Statistics Arkansas State University P.O. Box 70 State University, AR. 72467

[R] k-means cluster and plot labels

Hi, For my data, I followed the example of http://en.wikibooks.org/wiki/Data_Mining_Algorithms_In_R/Clustering/K-Means#Execution and got some very nice results. Despite the fact, that I want to achieve a bit more by clustering my data (stratification beyond case-control), the actual

Re: [R] k-means cluster and plot labels

Try the pch() argument to plot(), or perhaps using text(), depending on what exactly you're trying to achieve. Sarah On Tue, Dec 13, 2011 at 4:03 PM, Meesters, Christian meest...@aesku.com wrote: Hi, For my data, I followed the example of

[R] K means algorithm C code

Dear R user, How can I get the C or C++ source code of the R_kmeans_MacQueen or R_kmeans_Lloyd subroutines implemented in the R kmeans function of the R stats-package {stats}? Would these be available as a C header file (*.h) somewhere from the R installation??? Any help to get a C

Re: [R] K means algorithm C code

See Ligges, U. (2006): R Help Desk: Accessing the Sources. R News 6 (4), 43-45. Best, Uwe Ligges On 07.04.2011 16:05, Jean-Eudes Dazard wrote: Dear R user, How can I get the C or C++ source code of the R_kmeans_MacQueen or R_kmeans_Lloyd subroutines implemented in the R kmeans

[R] K-means result - variance between cluster

Hi, I like to present the results from the clustering method k-means in terms of variances: within and between Cluster. The k-means object gives only the within cluster sum of squares by cluster, so the between variance part is missing,for calculation the following table, which I try to get.

Re: [R] K-means result - variance between cluster

Dear Ralph, between and within clusters sum of squares (if you want variances, you need to divide them by the appropriate constant!) add up to the overall sum of squares, so you can get the beween clusters ss by computing the overall ss (one possibility to get this is to run kmeans with k=1)

Re: [R] K-means result - variance between cluster

On Fri, Jul 2, 2010 at 4:37 AM, Ralph Modjesch ralph.modje...@pfeiffer-koberstein-immobilien.de wrote: Hi, I like to present the results from the clustering method k-means in terms of variances: within and between Cluster. The k-means object gives only the within cluster sum of squares by

[R] K-means recluster data with given cluster centers

K-means recluster data with given cluster centers Dear R user, I have several large data sets. Over time additional new data sets will be created. I want to cluster all the data in a similar/ identical way with the k-means algorithm. With the first data set I will find my cluster centers and

Re: [R] K-means recluster data with given cluster centers

That kmeans returns an error if there is an empty cluster is a bit of a nuisance. It should not be too difficult to get rid off the kmeans function for what you call reclustering. You could write your own function that assigns every point of the new data to the closest initial center. That

[R] K-means clustering with NA

I am running a k-means clustering code in R : mydata_kmeans5 - kmeans(mydata, centers=5).. But the problem is that the data is having some NA in it. So R is showing me a message :Error in switch(nmeth, { : NA/NaN/Inf in foreign function call (arg 1) In addition: Warning messages: 1: In

[R] K-Means Clustering

Hello, I am hoping you can help me with a question concerning kmeans clustering in R. I am working with the following data-set (abbreviated): BMW Ford Infiniti Jeep Lexus Chrysler Mercedes Saab Porsche Volvo [1,] 6828 4544 7

Re: [R] K-Means Clustering

On 9 May 2008, at 09:12, Jordan van Rijn wrote: Hello, I am hoping you can help me with a question concerning kmeans clustering in R. I am working with the following data-set (abbreviated): BMW Ford Infiniti Jeep Lexus Chrysler Mercedes Saab Porsche Volvo [1,] 6

Re: [R] K-Means Clustering

Unfortunately, your data is *not* numeric. That is what the first error message, 'x' must be numeric, is telling you, and you should believe it. It might look numeric, but it isn't, which is why Ingmar mentioned you might have factors instead of numbers. Your challenge is to discover why.

[R] k-means: should columns in dataset be in same scale?

Hi all, Simple question re k-means. If I have a data set with columns that are on different scales (say col 1 has var=100 and col2 var=2), will this make a difference to the k-means algorithm? It seems as though it does. If so, should we first standardize the columns of the dataset so that each

Re: [R] k-means: should columns in dataset be in same scale?

k-means uses Euclidean distance, so scaling of the variables does matter. Whether you want to standardize depends on the example (as it does in most multivariate analysis problems, e.g. PCA has the same issues). On Tue, 22 Apr 2008, Johan Jackson wrote: Hi all, Simple question re k-means. If

[R] K Means Clustering Weighted by Frequency

*Apologies if this is not the right way to ask a question, I'm a first timer posting here. Does anyone have a solution to this? I'm having trouble figuring out how to use weighting with K Means Clustering. So say if my dataset is: Column 1 = x coords Column 2 = y coords Column 3 =