ClustanMDS ... is our
implementation of Bell Labs' MDSCAL and KYST, which we have translated and optimized for Windows - three clicks and you're configured.
What is multidimensional scaling?
Multidimensional scaling is the problem of representing n objects geometrically by n points, such that the inter-point distances correspond in some sense to experimental
similarities or dissimilarities between the objects. The underlying hypothesis is that the dissimilarities and distances are monotonically related. A goodness-of-fit criterion
called "stress" measures the extent to which the rank order of the dissimilarities corresponds to the rank order of the distances, and the MDS procedure computes a
configuration of points that minimizes the "stress" function. The objective is to obtain a scatter diagram, or plot, of your cases in two or more dimensions which describes the
relationships between them and their clusters.
For example, suppose you want to display graphically the
relationships between the 5-cluster model of Mammals according to the composition of their milk. Simply highlight the 5-cluster model on your tree and run MDS. The cluster model will then be displayed on an MDS scatterplot (left).
In this example, each cross corresponds to a case (species), colour coded by cluster, and the 5 clusters are identified by their
exemplars (Orangutan, Zebra, Fox, Deer and Seal). The scatterplot also gives us the clue that there
are two outliers (Elephant and Rabbit), which show up at the 7-cluster partition as singletons.
To run ClustanMDS, simply read in or compute a proximity matrix, then ...
1. Click "MDS" in the Prox menu ...
2. Click "Start" in the MDS dialogue
3. Click "Finish" in the MDS dialogue ...
... and your optimized MDS two-dimensional configuration is displayed. Hence our claim
three clicks and you're configured !
For further information about ClustanMDS, click below ...
To order ClustanMDS with ClustanGraphics, click here
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