K-Means Clustering with Matlab

Data Mining/01.04.2013/Sistem Informasi

You can see the explanation: http://en.wikipedia.org/wiki/K-means_clustering. K-means is hard-clustering that different with Fuzzy C-Means that Soft-Clustering.

File – New – GUI. Make a design below.

Save yout GUI.

Fill script to function ambildata_Callback:

  • data=uigetfile(‘*.xlsx’)
  • set(handles.data,‘String’,data)
  • X=xlsread(data)
  • handles.X=X
  • guidata(hObject,handles)

 

Look at command window to see the result

Script function data_Callback (text box of number of cluster)

Make sure k and handles.k appear in Command Window.

IDX and C the result of kmeans function that state index of every record and center of cluster respectively.

Look at how to create excel file with function xlswrite. There are two sheets: hasil and kluster. Use “set” for sending result to edit text ipa1, ipa2, ips1, and ips2 at GUI.

You can add axes to show the result graphically.

  • %buat grafik
  • ukuran=size(hasil)
  • jlhdata=ukuran(1,1)
  • axes(handles.axes1)
  • hold
  • for i=1:jlhdata
  • if hasil(i,3)==1
  • plot(hasil(i,1),hasil(i,2),‘*r’)
  • else
  • plot(hasil(i,1),hasil(i,2),‘*b’)
  • end
  • end
  • plot(C(1,1),C(1,2),‘ok’)
  • plot(C(2,1),C(2,2),‘ok’)

Next week we’ll discuss Fuzzy C-Means Clustering.

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3 thoughts on “K-Means Clustering with Matlab

  1. Pak, saya mau bertanya
    Kalau untuk code program “buat grafik” itu ditaruhnya dimana ya Pak? Soalnya saya baru berhasil mempraktikkan sampai data hasil kesimpan.
    Terimakasih sebelumnya

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