I´d like to know if I have understood the algorithm of k-means
clustering: Is it all right that if k has the same number like OTUs
then k-means will work like UPGMA?
Which data type needs k-means cluster algorithm? A ultrametric distance
matrix?
Re: K-means and SOM ...Greg Heath wrote: ... >> I would like to know, in what way clustering achieved by K-means is ... there are several K-means objective... > You'll have to search for that algorithm,... (comp.soft-sys.matlab)
Re: Clustering Software ... past decades that could be attributed to the use of the clustering... a consensus that average linkage clustering produces worse results ... If the algorithm had been the MIN, ... and the similarity matrix reduces to a size one less, ... (sci.stat.math)
Re: Understanding k-mean++ ... Somewhere you can find a random number generator which will generate uniform random variates r in the range ... Ten or more years ago, I participated in a discussion on initialisation for fuzzy k-means clustering: ... (comp.graphics.algorithms)
Re: Clustering Software ... In the evolutionary sense things can be primitive yet satisfactory. ... past decades that could be attributed to the use of the clustering... If the algorithm had been the MIN, ... and the similarity matrix reduces to a size one less, ... (sci.stat.math)
Re: NP-hardness of k-means clustering ... > I checked the compendium first of all, ... This one is the closest to k-means....clustering algorithm as implied in the *references*, ...Eray Ozkural... (comp.theory)
