Hi folks, I have to respectfully disagree in part with Fredrik's comments.
I totally agree with him that K-Means does not provide a unique solution. Repeated clustering to determine the stability of a solution is wise council. I think, however, that Frederik is off re the relationship between clustering and discriminant analysis. In discrim, you start with cases that have been assigned a priori to groups and the analysis seeks to find optimal (linear) combinations of predictor variables that properly assign cases to the groups. It's sort of like multiple regression with a nominal dependent variable. Well, sort of . . . What Jason has requested (as I have in a previous note) is a vector of scores that identifies which cases fall into which cluster. One can then look at the distinguishing characteristics of each cluster by cross-tabbing, AOVing, etc. the cluster assignment score against other variables. Without the cluster assignment scores for further analysis, doing K-Means -- or any kind of clustering procedure, e.g. Q-type factor analysis -- is somewhere between relatively and totally useless. At least in my not so humble estimation. Cheers, Mark On Sep 12, 2013, at 12:00 PM, [email protected] wrote: Send Pspp-users mailing list submissions to [email protected] To subscribe or unsubscribe via the World Wide Web, visit https://lists.gnu.org/mailman/listinfo/pspp-users or, via email, send a message with subject or body 'help' to [email protected] You can reach the person managing the list at [email protected] When replying, please edit your Subject line so it is more specific than "Re: Contents of Pspp-users digest..." Today's Topics: 1. PSPP K-means quick-cluster: assigning cases (Fredrik Clementz) ---------------------------------------------------------------------- Message: 1 Date: Thu, 12 Sep 2013 14:02:01 +0200 From: Fredrik Clementz <[email protected]> To: [email protected], "[email protected]" <[email protected]> Subject: PSPP K-means quick-cluster: assigning cases Message-ID: <CA+y-Rt-WGxteonyFvLsJeyaeGtOzM8no22BiGLqv_Q=hlaf...@mail.gmail.com> Content-Type: text/plain; charset="iso-8859-1" Hi Jason, The feature you're looking for is Discriminant analysis and is unfortunately not implemented in PSPP. I also have to mention that you should be vary about using K-means as a clustering technique. Please rerandomize data and run several times to see if results are similar as the technique is dependant on how the data i sorted. Cheers, -- Fredrik -------------- next part -------------- An HTML attachment was scrubbed... URL: <http://lists.gnu.org/archive/html/pspp-users/attachments/20130912/e0405bd1/attachment.html> ------------------------------ _______________________________________________ Pspp-users mailing list [email protected] https://lists.gnu.org/mailman/listinfo/pspp-users End of Pspp-users Digest, Vol 88, Issue 10 ****************************************** _______________________________________________ Pspp-users mailing list [email protected] https://lists.gnu.org/mailman/listinfo/pspp-users
