I have carried out PCA and then clustered the 6 resultant components using K-means clustering technique using SPSS. Normally SPSS adds a class variable for each case indicating its assigned group.

Is there any other method I can "calculate" the class variable (i.e. using component scores and REGR factor scores for the K means analysis given in the "Final Cluster centers" table????

  • $\begingroup$ Please break down your last sentence into clear parts. $\endgroup$ – rolando2 Jul 5 '11 at 3:16
  • $\begingroup$ Do I understand you right in that you ask how to classify new objects to the k clusters given that you have the k cluster means? $\endgroup$ – ttnphns Jul 5 '11 at 5:57
  • $\begingroup$ Sorry for not being clear. Exactly ttnphns. K-means analysis gives a table titled "final Cluster Centers" in the output. On the basis of these centers, all cases are classified. Just wanted to know what are the calculations involved. Thanks. $\endgroup$ – mzalikhan Jul 5 '11 at 7:09
  • $\begingroup$ Below you find my technical answer how to classify new objects to the existing clusters. Object is assigned to cluster which center it is most close to. $\endgroup$ – ttnphns Jul 5 '11 at 7:30

Rerun your clusterization to save the final cluster centers as .SAV data file (check "Write final"). Then you open the data file with new objects to classify (this dataset may contain only new objects or a mix of new and old objects - it will make no difference). Check "Read initial" and choose here that saved file with cluster centers. Check "Classify only" instead of "Iterate and classify". Order to save cluster memberships under "Save" button. Run.


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