48#ifndef GUM_LEARNING_SCORE_BDEU_H
49#define GUM_LEARNING_SCORE_BDEU_H
106 const std::vector< std::pair< std::size_t, std::size_t > >&
ranges,
213#ifndef DOXYGEN_SHOULD_SKIP_THIS
the internal prior for the BDeu score (N' / (r_i * q_i)
The class for computing Log2 (Gamma(x)).
the internal prior for the BDeu score (N' / (r_i * q_i)
the class used to read a row in the database and to transform it into a set of DBRow instances that c...
A class for storing a pair of sets of NodeIds, the second one corresponding to a conditional set.
the base class for all a priori
ScoreBDeu(const ScoreBDeu &from)
copy constructor
ScoreBDeu(const DBRowGeneratorParser &parser, const Prior &prior, const Bijection< NodeId, std::size_t > &nodeId2columns=Bijection< NodeId, std::size_t >())
default constructor
void setEffectiveSampleSize(double ess)
sets the effective sample size of the internal prior
ScoreBDeu & operator=(ScoreBDeu &&from)
move operator
std::string isPriorCompatible() const final
indicates whether the prior is compatible (meaningful) with the score
ScoreBDeu & operator=(const ScoreBDeu &from)
copy operator
virtual ~ScoreBDeu()
destructor
virtual double score_(const IdCondSet &idset) final
returns the score for a given IdCondSet
ScoreBDeu(ScoreBDeu &&from)
move constructor
virtual ScoreBDeu * clone() const
virtual copy constructor
ScoreBDeu(const DBRowGeneratorParser &parser, const Prior &prior, const std::vector< std::pair< std::size_t, std::size_t > > &ranges, const Bijection< NodeId, std::size_t > &nodeId2columns=Bijection< NodeId, std::size_t >())
default constructor
const Prior & internalPrior() const final
returns the internal prior of the score
const std::vector< std::pair< std::size_t, std::size_t > > & ranges() const
returns the current ranges
Score(const DBRowGeneratorParser &parser, const Prior &external_prior, const std::vector< std::pair< std::size_t, std::size_t > > &ranges, const Bijection< NodeId, std::size_t > &nodeId2columns=Bijection< NodeId, std::size_t >())
default constructor
The class for computing Log2 (Gamma(x)).
include the inlined functions if necessary
gum is the global namespace for all aGrUM entities
the class for computing BDeu scores
the base class for all the scores used for learning (BIC, BDeu, etc)