50#ifndef GUM_IMPORTANCE_INFERENCE_H
51#define GUM_IMPORTANCE_INFERENCE_H
70 template <
typename GUM_SCALAR >
132#ifndef GUM_NO_EXTERN_TEMPLATE_CLASS
double epsilon() const override
Returns the value of epsilon.
Portion of a BN identified by the list of nodes and a BayesNet.
Class representing the minimal interface for Bayesian network with no numerical data.
void onContextualize_(BayesNetFragment< GUM_SCALAR > *bn) override
fired when Bayesian network is contextualized
Instantiation burnIn_() override
draws a defined number of samples without updating the estimators
void unsharpenBN_(BayesNetFragment< GUM_SCALAR > *bn, float epsilon)
modifies the cpts of a BN in order to tend to uniform distributions
ImportanceSampling(const IBayesNet< GUM_SCALAR > *bn)
Default constructor.
~ImportanceSampling() override
Destructor.
Instantiation draw_(GUM_SCALAR *w, Instantiation prev) override
draws a sample according to Importance sampling
Class for assigning/browsing values to tuples of discrete variables.
SamplingInference(const IBayesNet< GUM_SCALAR > *bn)
default constructor
Implementation of Importance Sampling for inference in Bayesian networks.
gum is the global namespace for all aGrUM entities
This file contains general methods for simulation-oriented approximate inference.