# Uses of Class
org.apache.lucene.search.similarities.SimilarityBase

Packages that use SimilarityBase
Package
Description
org.apache.lucene.search.similarities
This package contains the various ranking models that can be used in Lucene.

## Uses of SimilarityBase in org.apache.lucene.search.similarities

Subclasses of SimilarityBase in org.apache.lucene.search.similarities
Modifier and Type
Class
Description
`class`
`Axiomatic`
Axiomatic approaches for IR.
`class`
`AxiomaticF1EXP`
F1EXP is defined as Sum(tf(term_doc_freq)*ln(docLen)*IDF(term)) where IDF(t) = pow((N+1)/df(t), k) N=total num of docs, df=doc freq
`class`
`AxiomaticF1LOG`
F1LOG is defined as Sum(tf(term_doc_freq)*ln(docLen)*IDF(term)) where IDF(t) = ln((N+1)/df(t)) N=total num of docs, df=doc freq
`class`
`AxiomaticF2EXP`
F2EXP is defined as Sum(tfln(term_doc_freq, docLen)*IDF(term)) where IDF(t) = pow((N+1)/df(t), k) N=total num of docs, df=doc freq
`class`
`AxiomaticF2LOG`
F2EXP is defined as Sum(tfln(term_doc_freq, docLen)*IDF(term)) where IDF(t) = ln((N+1)/df(t)) N=total num of docs, df=doc freq
`class`
`AxiomaticF3EXP`
F3EXP is defined as Sum(tf(term_doc_freq)*IDF(term)-gamma(docLen, queryLen)) where IDF(t) = pow((N+1)/df(t), k) N=total num of docs, df=doc freq gamma(docLen, queryLen) = (docLen-queryLen)*queryLen*s/avdl NOTE: the gamma function of this similarity creates negative scores
`class`
`AxiomaticF3LOG`
F3EXP is defined as Sum(tf(term_doc_freq)*IDF(term)-gamma(docLen, queryLen)) where IDF(t) = ln((N+1)/df(t)) N=total num of docs, df=doc freq gamma(docLen, queryLen) = (docLen-queryLen)*queryLen*s/avdl NOTE: the gamma function of this similarity creates negative scores
`class`
`DFISimilarity`
Implements the Divergence from Independence (DFI) model based on Chi-square statistics (i.e., standardized Chi-squared distance from independence in term frequency tf).
`class`
`DFRSimilarity`
Implements the divergence from randomness (DFR) framework introduced in Gianni Amati and Cornelis Joost Van Rijsbergen.
`class`
`IBSimilarity`
Provides a framework for the family of information-based models, as described in Stéphane Clinchant and Eric Gaussier.
`class`
`IndriDirichletSimilarity`
Bayesian smoothing using Dirichlet priors as implemented in the Indri Search engine (http://www.lemurproject.org/indri.php).
`class`
`LMDirichletSimilarity`
Bayesian smoothing using Dirichlet priors.
`class`
`LMJelinekMercerSimilarity`
Language model based on the Jelinek-Mercer smoothing method.
`class`
`LMSimilarity`
Abstract superclass for language modeling Similarities.