Is there an clustering algorithm with which I can declare expected centroid in advance?

Hi Friends,

      I need to Cluster a dataset by declaring the centroids before starting a cluster itself. For eg:
      Dataset includes {A,B,C,D,E,F}
A=(1,1)
B=(1.1,1.1)
C=(.9,.9)
D=(10,10)
E=(10.1,10.1)
F=(9.9,9.9)

     I want to know the nearby values to B data Point. So Please let me know if there

Answer 1

[Massimo Zanetti]

The k-means clustering is what you need. You can start the algorithm by selecting your own initial centroids by setting the parameter 'Start' to a matrix in which rows are your centroids.

Read carefully the documentation.