[Forum SIS] Bocconi DEC Seminar: Christian Hennig - November 10th

[Anna Simoni]

Dear colleagues, 

The Department of Decision Sciences (DEC) of Bocconi University is pleased to invite you to the seminar: 
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DEC Seminar 
Università Bocconi, 
Room 3-E4-SR03 
Via Rontgen 1 - 3rd floor 
Time: 12:30pm 

Thursday, November 10th 

Christian Hennig 
(Department of Statistical Science, University College London) 

"How to find the best cluster analysis method (for social stratification based on mixed type data)?" 


Abstract 

This presentation will treat two issues. 
1. A general approach for the decision about the "best" cluster analysis method will be sketched. 
This is based on the idea that a subjective decision is needed about the cluster concept required in a particular application, and that there is no such thing as an objectively true clustering determined by the data alone. 
For example, even if data can be perfectly fitted by a Gaussian mixture, this does not necessarily mean that the mixture components correspond to the "true" clusters, because in a given application unimodal mixtures of more than one Gaussian may be considered as a single cluster (see Hennig 2010). 
On the other hand, large within-cluster dissimilarities may not be admissible, in which case certain Gaussian components need to be split up. 
2. The general philosophy is applied to the problem of defining social strata from data with mixed continuous, ordinal and categorical variables. 
Clusterings as obtained from a mixture/latent class approach (as for example fitted by the LatentGOLD software, Vermunt and Magidson, 2005) are compared with clusterings obtained from applying $k$-medoids (Kaufman and Rousseeuw, 1990) to dissimilarities balancing the different types of variables in a sensible user-specified way. 

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Sincerely, 
Anna Simoni 



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Anna Simoni 

Assistant Professor 
Department of Decision Sciences 
Università Bocconi 
via Roentgen, 1 
20136 Milano - Italy 

Webpage: http://sites.google.com/site/simonianna/home 

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