From: | Tomas Vondra <tv(at)fuzzy(dot)cz> |
---|---|
To: | pgsql-students(at)postgresql(dot)org |
Subject: | Re: : Fuzzy C means algorithms in MAdlib |
Date: | 2013-05-01 22:04:27 |
Message-ID: | 5181916B.3080203@fuzzy.cz |
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Lists: | pgsql-students |
On 27.4.2013 12:36, Akansha Singh 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 centroids are updated based
> on the classified samples. In a variation of this approach known as
> fuzzy c-means, all vectors have a degree of membership for each
> cluster, and the respective centroids are calculated based on these
> membership degrees.
>
> Whereas the K-means algorithm computes the average of the vectors in
> a cluster as the center, fuzzy c-means finds the center as a weighted
> average of all points, using the membership probabilities for each
> point as weights. Vectors with a high probability of belonging to the
> class have larger weights, and more influence on the centroid.
While I'm a fan of data analysis, I'm still struggling with a question
why this should be implemented as a PostgreSQL GSoC project. What would
be the result? An update to MADlib, implementing k-means, or somethink
like a PostgreSQL extension?
regards
Tomas
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