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

SelimSelim Member Posts: 32 Contributor I
edited June 14 in Help
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 
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_ADavid_A Moderator, Employee, RMResearcher, Member Posts: 170  RM Research

    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.


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