Implementations of this interface have a printable representation and certain attributes that are common across all clustering implementations
A model is a probability distribution over observed data points and allows the probability of any data point to be computed.
A model distribution allows us to sample a model from its prior distribution.
An online Gaussian statistics accumulator based upon Knuth (who cites Welford) which is declared to be numerically-stable.
An online Gaussian accumulator that uses a running power sums approach as reported on http://en.wikipedia.org/wiki/Standard_deviation Suffers from overflow, underflow and roundoff error but has minimal observe-time overhead
Output of each clustering algorithm is either a hard or soft assignment of items to clusters.
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