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On 27-Apr-2013, at 16:04, Akansha Singh <akansha.singh@oracle.com> wrote:
> HI
> I would like to know can this algorithm be implemented on MAdlIB
> In the K-means algorithm, each vector is classified as belonging to a single cluster (hard clustering), and the
centroidsare updated based on the classified samples. In a variation of this approach known as fuzzy c-means [2, 29],
allvectors have a degree of membership for each cluster, and the respective centroids are calculated based on these
membershipdegrees.
>
> Whereas the K-means algorithm computes the average of the vectors in a cluster as the center, fuzzy c-means finds the
centeras a weighted average of all points, using the membership probabilities for each point as weights. Vectors with a
highprobability of belonging to the class have larger weights, and more influence on the centroid.
I would suggest marking the MADlib devel list as well.
This seems like an easy to do variation of k means, and should be doable and built over the existing k means resources
inMADLib.
Regards,
Atri
