how can ? convert to execute python k-means algorythm to x-means and k-means algorthm ?

Selim

hello everybody , ı have doing k-means clustering via execute python operator but ı want to apply to this process k-medoid and x-means so ı need to change to k-means code section in my python screen so what ı need to write code for x-means and k-medoid to k-means execute python screen .ı have shared my python screen 
-------------code----------------

import pandas as pd

from operator import itemgetter

import numpy as np

import random

import sys

from scipy.spatial import distance

from sklearn.cluster import KMeans

C = 10

def k_means(X) : 

  kmeans = KMeans(n_clusters=C, random_state=0).fit(X)

  return kmeans.cluster_centers_

def samevolumecluster( D, volumes):

    """ in: point-to-cluster-centre distances D, Npt x C

            

        out: xtoc, X -> C, equal-size clusters

       

    """

    

    clustervolume = (np.sum(volumes)) / C

    xcd = list( np.ndenumerate(D) )  # ((0,0), d00), ((0,1), d01) ...

  

    xcd.sort( key=itemgetter(1) )

    xtoc = np.ones( Npt, int ) * -1

    nincluster = np.zeros( C, int )

    vincluster = np.zeros( C, int)

    nall = 0

    for (x,c), d in xcd:

        

        if xtoc[x] < 0 and vincluster[c] <= clustervolume+10:

 

            xtoc[x] = c

            nincluster[c] += 1

            

            vincluster[c] += volumes[x]

            nall += 1

            if nall >= Npt:  break

    return xtoc

def rm_main(data):

 

  data_2 = data.values

  volumes = data_2[:,1]

  centres = k_means(data_2)

  D = distance.cdist( data_2, centres)

  xtoc = samevolumecluster( D, volumes)

  data['cluster'] = xtoc

  return data

David_A

Hi,

did you know that there is no need to code these clustering algorithms by yourself.

RapidMiner has a lot of clustering methods as build in, ready to use, operators.

Best,
David