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EG Cluster-IT™ is a utility to reduce a large number of points into natural clusters. 

What is a cluster? There are several esoteric definitions of clusters available, but building from an analogy of populations seems the most appropriate.

Given a map of the top 10,000 populated places on the earth, it is clear that definite patterns appear.These patterns are clusters and are usually qualitatively observed.

To quantitatively define clusters, parameters that define, induce and limit the formation of clusters are introduced. Since the definition of a cluster is subjective, the parameters tailor the results to your particular definition and, ultimately, your objective.

Parameter Types
EG Cluster-IT includes two types of parameters - limiting and threshold.  Limiting parameters control what is taken into account in forming clusters.

Threshold parameters stop processing when specific events occur such as when a specific number of clusters are reached or when a cluster of a certain size is reached. Threshold parameters are typically used in online applications.

Weighting Points
Returning to the populated places analogy, how can differing populations be handled? For example, the Los Angeles area is comprised of many individual cities with Los Angeles by far being the largest. In other words, Los Angeles overwhelms all of the other cities in the "area".

EG Cluster-IT handles weighted points by including the weights in the cluster calculations. In fact, in this Los Angeles example, the resulting cluster for the Los Angeles area is very close to the center of Los Angeles itself (as you might expect.)

Versions
There are three versions of Cluster-IT

  1. The first version contains the basic functionality.
  2. The second version adds threshold capabilities.
  3. The third version adds a 32bit callable DLL.

 

Above: 707 initial points, representing delivery destinations.
Each point has a weight (in lbs) associated with it.

Below: After running Cluster-IT!, 22 clusters were identified.

 

 

 

 

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