Cluster Analysis Gets Complicated
 
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Description:

Cluster analysis is widely used in segmentation studies for several reasons. First of all, it's easy to use.  In addition, there are many variations of the method, most statistical packages have a clustering option, and for the most part it's a good analytical technique. Further,  the non-hierarchical clustering technique K-means is particularly popular because it's very fast and can handle large data sets. CLuster analysis is a distance-based method because it uses Euclidean distance ( or some variant) in multidimensional space to assign objects to clusters to which they are closest. However, collinearity can become a major problem when such distance based measures are used. It poses a serious problem that, unless addresses, can produce distorted results.

Submitted On:

20 Sep 2006

Submitted By:

Administrator (admin)

File Date:

20 Sep 2006

File Size:

187.36 Kb

File Type:

pdf

Downloads:

32