Uses of Class
org.terrier.matching.models.normalisation.Normalisation

Packages that use Normalisation

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

Uses of Normalisation in org.terrier.matching.models

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

Modifier and Type	Field and Description
protected Normalisation[]	PerFieldNormWeightingModel.fieldNormalisations
protected Normalisation	DFRWeightingModel.normalisation The applied frequency normalisation method.

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

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

Uses of Normalisation in org.terrier.matching.models.normalisation

Subclasses of Normalisation in org.terrier.matching.models.normalisation

Modifier and Type	Class and Description
class	Normalisation0 This class implements an empty normalisation.
class	Normalisation1 This class implements the DFR normalisation 1, which is identical to DFR normalisation 2 with c=1.0
class	Normalisation2 This class implements the DFR normalisation 2.
class	Normalisation2exp This class implements the DFR normalisation 2 with natural logorithm.
class	Normalisation3 This class implements the Dirichlet Priors normalisation.
class	NormalisationB This class implements BM25's normalisation method.
class	NormalisationF This class implements an increasing density function for the frequency normalisation.
class	NormalisationJ This class implements the tf normalisation based on Jelinek-Mercer smoothing for language modelling.
class	NormalisationJN This class implements the tf normalisation based on Jelinek-Mercer smoothing for language modelling where collection model is given by document frequency instead of term frequency.
class	NormalisationP This class implements Term Frequency Normalisation via Pareto Distributions
class	NormalisationStatic This class implements a Normalisation method that forces all term frequencies to the value of the parameter.

Methods in org.terrier.matching.models.normalisation that return Normalisation

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