Finding a pattern in high dimensional data

Hi,

I have a simulation of an algorithm working on a list of objects. Each
object has a priority which reflects how much that particular object is
being used.
Here is an example of some sample data with 4 objects in a list. The first
set in each line is the priorities and the second set in each line is the
resulting usage frequency {{p1,p2,p3,p4},{f1,f2,f3,f4}}.

{{1,2,10,10},{0.0909,0.0909,0.4091,0.4091}}
{{1,2,11,10},{0.0833,0.0833,0.4167,0.4167}}
{{1,2,10,12},{0.0800,0.0800,0.2800,0.5600}}
{{1,2,11,1},{0.0909,0.0909,0.7273,0.0909}}
{{1,2,11,2},{0.0909,0.0909,0.7273,0.0909}}
{{1,2,11,3},{0.0909,0.0909,0.7272,0.0909}}
{{1,2,11,4},{0.0909,0.0909,0.7046,0.1136}}
{{1,2,11,5},{0.0870,0.0870,0.6956,0.1304}}
{{1,2,11,6},{0.0833,0.0834,0.6667,0.1666}}
{{7,1,2,11},{0.1818,0.0909,0.0909,0.6364}}
{{1,2,11,8},{0.0909,0.0909,0.5909,0.2273}}
{{9,1,2,11},{0.2727,0.0909,0.0909,0.5455}}
{{1,2,11,10},{0.0833,0.0833,0.4167,0.4167}}
{{1,2,11,11},{0.0833,0.0833,0.4167,0.4167}}
{{1,2,11,12},{0.0833,0.0833,0.4167,0.4167}}

I can create as much data as I want with as many elements as I want.

What I would like to do is to find a pattern. More precisely: How does the
set of usage frequencies depend of the set of priorities. I don't know much
about multivariate data analysis so any hint on where to start or what to
read about would be most helpful.

Thanks in advance.


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