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CMPS-242 2016
We will need a second evaluation method that involves data not in our ground truth.
We may have to use human evaluation.
Maybe something like get a collection of 100 or so random restaurants and then have humans give some similarity/cluster information.
They are sucking pretty hard, do some analysis.
Maybe just weight them low.
Create a website/github project page, that fleshes out the paper
Learn some feature weights.
Think about it.
Maybe try a density based clustering model, so that you don't have to specify the number of clusters.
If we have < 200 (guessing) data points, then we can do everything in < 1sec.
This would be great for weight learning.
Will the rand index make sense with only 200 points?
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