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For sampling from Bayesian networks
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Inherited from Inherited from |
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_condition_index Instantiated variables have their values, others have None |
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_cpts For each variable, its CPT (in topological order). |
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_dists For each variable, a dictionary mapping parent instantiations to a MultinomialSampler object |
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_indextuple The tuple (0,1, ...n) where n is the number of variables |
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_indices For each variable, a tuple of the indices corresponding to its parents |
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_instskel A list of Nones of the right length to hold a full joint instantiation. |
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_var2index Maps a variable to its index in _variables
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_variables An ordering of the DN's variables used for example, for Gibbs sampling |
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Inherited from |
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Construct a sampler from a dependency network
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Forward sample from an (unconditional) BN
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Importance sample from a BN
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Rejection sample from a BN
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_cptsFor each variable, its CPT (in topological order). CPTs are not Parameters.CPT objects.self._cpts[i][parent_inst][cond] is the probability
of the ith variable taking value cond when its
parents have instantiation parent_inst, where
parent_inst is a tuple of parent values.
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_var2indexMaps a variable to its index in_variables
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