This class implements the In_expB2 weighting model, namely Inverse Expected Document Frequency model with
Bernoulli after-effect and normalisation 2. The logarithms are base 2. This model can be
used for classic ad-hoc tasks.
the score assigned to a document with the given tf and
docLength, and other preset parameters
public final double score(double tf,
This method provides the contract for implementing weighting models.
As of Terrier 3.6, the 5-parameter score method is being deprecated
since it is not used. The two parameter score method should be used
instead. Tagged for removal in a later version.