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Mixture of Full Gaussians Model is a subclass of the Mixture of Gaussians
Model which only uses full covariances in its fitness compuations. If it
fails in it's computation, then a log-likelihood score of -1e38 is returned.
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Methods
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__init__
evaluateFitness
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__init__
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__init__ (
self,
k,
means,
covariances,
weights=None,
)
Creates a new Mixture of Full Gaussians (MoFG) Model, containing k
Gaussian clusters in d-dimensional space.
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evaluateFitness
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evaluateFitness ( self, data )
Return the fitness of the model given a paricular set of data. Using only
the full covariance matrix, if that fails, then the log-likelihood is set
to -MAX_FLOAT =~ -1e38.
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