Uses of Class
org.terrier.matching.models.basicmodel.BasicModel

Packages that use BasicModel

Package	Description
org.terrier.matching.models	Provides the classes that implement various weighting models.
org.terrier.matching.models.basicmodel	Provides the interface and the classes for implementing the basic models for randomness in the DFR framework.

Uses of BasicModel in org.terrier.matching.models

Fields in org.terrier.matching.models declared as BasicModel

Modifier and Type	Field and Description
protected BasicModel	PerFieldNormWeightingModel.basicModel
protected BasicModel	DFRWeightingModel.basicModel The applied basic model for randomness.

Constructor parameters in org.terrier.matching.models with type arguments of type BasicModel

Constructor and Description
PerFieldNormWeightingModel(Class<? extends BasicModel> _basicModel, Class<? extends Normalisation> _normalisationModel) Constructs an instance of PerFieldNormWeightingModel

Uses of BasicModel in org.terrier.matching.models.basicmodel

Subclasses of BasicModel in org.terrier.matching.models.basicmodel

Modifier and Type	Class and Description
class	B This class implements the B basic model for randomness.
class	BM This class implements the BM weighting model, which generates the original weight given by the BM25 formula, without frequency normalisation and query term weighting.
class	Br This class implements the Bernoulli model of randomness
class	DFR_BM This class implements the DFR BM weighting model, which is an approximation of BM25 in the DFR framework.
class	IF This class implements the IF basic model for randomness.
class	In This class implements the In basic model for randomness.
class	In_exp This class implements the In_exp basic model for randomness.
class	P This class implements the P basic model for randomness.
class	PL This class implements the PL weighting model.

Methods in org.terrier.matching.models.basicmodel that return BasicModel

Modifier and Type	Method and Description
BasicModel	BasicModel.clone() Clone this weighting model