[R] algorithm used in k-mean clustering

2005-04-22 Thread Asha Jayanthi
Hi,
I have used the kmean fucntion in R to produce some results for my analysis.
I like to know the specific underlying algorithm used for the implementation 
of the function kmean in R. I tried looking for some documents but could not 
find any.

I obtained the kmean result for k ranging from 2 to 10. When i did this 
initally it worked perfectly. When i tried running again i get the error

Error: empty cluster: try a better set of initial centers
and i have not changed anything in the code. And i get this error only for k 
= 2 and 10.

does anyone know why it worked well intially and failed now?
Asha
Will he be rookie of the year?
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Re: [R] algorithm used in k-mean clustering

2005-04-22 Thread Gavin Simpson
Asha Jayanthi wrote:
Hi,
I have used the kmean fucntion in R to produce some results for my 
analysis.

I like to know the specific underlying algorithm used for the 
implementation of the function kmean in R. I tried looking for some 
documents but could not find any.

I obtained the kmean result for k ranging from 2 to 10. When i did this 
initally it worked perfectly. When i tried running again i get the error

Error: empty cluster: try a better set of initial centers
and i have not changed anything in the code. And i get this error only 
for k = 2 and 10.

does anyone know why it worked well intially and failed now?
Asha
help for all R functions available on your system can be viewed using 
?function_name - e.g. in your case ?kmeans displays the help for the 
kmeans function.

Doing this gives:
...
 centers: Either the number of clusters or a set of initial (distinct)
  cluster centres.  If a number, a random set of (distinct)
  rows in 'x' is chosen as the initial centres.
So the randomness you are experiencing is related to the choice of centers.
Search the archives of this mailing list as this question was asked 
recently - e.g. http://tolstoy.newcastle.edu.au/R/help/05/04/1692.html

Read all of ?kmeans as it has references for the algorithm used.
Gav
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