Re: : Fuzzy C means algorithms in MAdlib
От | Tomas Vondra |
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Тема | Re: : Fuzzy C means algorithms in MAdlib |
Дата | |
Msg-id | 5181916B.3080203@fuzzy.cz обсуждение исходный текст |
Ответ на | : Fuzzy C means algorithms in MAdlib (Akansha Singh <akansha.singh@oracle.com>) |
Список | 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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