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Description
Class Summary | |
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BB2 | This class implements the BB2 weighting model. |
BM25 | This class implements the Okapi BM25 weighting model. |
BM25F | A convenience subclass of PerFieldNormWeightingModel setup to do specifically BM25F, as described by [Zaragoza TREC-2004]. |
DFI0 | Implementation of the basic Divergence from Independence model. |
DFR_BM25 | This class implements the DFR_BM25 weighting model. |
DFRee | This class implements the DFRee weighting model. |
DFRWeightingModel | This class implements a modular Divergence from Randomness weighting model. |
DirichletLM | Bayesian smoothing with Dirichlet Prior. |
DLH | This class implements the DLH weighting model. |
DLH13 | This class implements the DLH13 weighting model. |
DPH | This class implements the DPH hypergeometric weighting model. |
Hiemstra_LM | This class implements the Hiemstra LM weighting model. |
Idf | This class computes the idf values for specific terms in the collection. |
IFB2 | This class implements the IFB2 weighting model. |
In_expB2 | This class implements the PL2 weighting model. |
In_expC2 | This class implements the In_expC2 weighting model. |
InB2 | This class implements the PL2 weighting model. |
InL2 | This class implements the InL2 weighting model. |
Js_KLs | This class implements the Js_KLs weighting model, which is the product of two measures: the Jefrreys' divergence with the Kullback Leibler's divergence. |
LemurTF_IDF | This class implements the TF_IDF weighting model as it is implemented in Lemur. |
LGD | This class implements the LGD weighting model. |
MDL2 | This class implements the MDL2 field-based weighting model. |
ML2 | This class implements the ML2 field-based weighting model. |
PerFieldNormWeightingModel | A class for generating arbitrary per-field normalisation models. |
PL2 | This class implements the PL2 weighting model. |
PL2F | A convenience subclass of PerFieldNormWeightingModel setup to do specifically PL2F. |
TF_IDF | This class implements the TF_IDF weighting model. |
WeightingModel | This class should be extended by the classes used for weighting terms and documents. |
WeightingModelFactory | A factory method for handling the initialisation of weighting models. |
XSqrA_M | This class implements the XSqrA_M weighting model, which computed the inner product of Pearson's X^2 with the information growth computed with the multinomial M. |
Provides the classes that implement various weighting models. Generally, the models fall into two classes:
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