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We assume that
the data was generated from a
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number of
different classes. The aim is to cluster
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data from the
same class together.
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How
do we decide the number of classes?
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Why
not put each datapoint into a separate class?
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What is the payoff for clustering things
together?
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What
if the classes are hierarchical?
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What
if each datavector can be classified in
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many
different ways? A one-out-of-N
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classification
is not nearly as informative as a
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feature
vector.
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