## 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 and 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` | `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.

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