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

- Packages that use Similarity
  Package | Description
  --- | ---
  org.apache.lucene.index | Code to maintain and access indices.
  org.apache.lucene.search | Code to search indices.
  org.apache.lucene.search.similarities | This package contains the various ranking models that can be used in Lucene.
  org.apache.lucene.search.spans | The calculus of spans.

- - ### Uses of Similarity in org.apache.lucene.index

    Fields in org.apache.lucene.index declared as Similarity
    Modifier and Type | Field and Description
    --- | ---
    `protected Similarity` | LiveIndexWriterConfig.`similarity` `Similarity` to use when encoding norms.

    Methods in org.apache.lucene.index that return Similarity
    Modifier and Type | Method and Description
    --- | ---
    `Similarity` | LiveIndexWriterConfig.`getSimilarity()` Expert: returns the `Similarity` implementation used by this `IndexWriter`.
    `Similarity` | IndexWriterConfig.`getSimilarity()`

    Methods in org.apache.lucene.index with parameters of type Similarity
    Modifier and Type | Method and Description
    --- | ---
    `IndexWriterConfig` | IndexWriterConfig.`setSimilarity(Similarity similarity)` Expert: set the `Similarity` implementation used by this IndexWriter.

  - ### Uses of Similarity in org.apache.lucene.search

    Methods in org.apache.lucene.search that return Similarity
    Modifier and Type | Method and Description
    --- | ---
    `static Similarity` | IndexSearcher.`getDefaultSimilarity()` Expert: returns a default Similarity instance.
    `Similarity` | IndexSearcher.`getSimilarity(boolean needsScores)` Expert: Get the `Similarity` to use to compute scores.

    Methods in org.apache.lucene.search with parameters of type Similarity
    Modifier and Type | Method and Description
    --- | ---
    `void` | IndexSearcher.`setSimilarity(Similarity similarity)` Expert: Set the Similarity implementation used by this IndexSearcher.

  - ### Uses of Similarity in org.apache.lucene.search.similarities

    Subclasses of Similarity 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` F2EXP 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
    `class` | `AxiomaticF3LOG` F2EXP 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
    `class` | `BM25Similarity` BM25 Similarity.
    `class` | `BooleanSimilarity` Simple similarity that gives terms a score that is equal to their query boost.
    `class` | `ClassicSimilarity` Expert: Default scoring implementation which `encodes` norm values as a single byte before being stored.
    `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.
    `class` | `MultiSimilarity` Implements the CombSUM method for combining evidence from multiple similarity values described in: Joseph A.
    `class` | `PerFieldSimilarityWrapper` Provides the ability to use a different `Similarity` for different fields.
    `class` | `SimilarityBase` A subclass of `Similarity` that provides a simplified API for its descendants.
    `class` | `TFIDFSimilarity` Implementation of `Similarity` with the Vector Space Model.

    Fields in org.apache.lucene.search.similarities declared as Similarity
    Modifier and Type | Field and Description
    --- | ---
    `protected Similarity` | PerFieldSimilarityWrapper.`defaultSim` Default similarity used for query norm and coordination factors.
    `protected Similarity[]` | MultiSimilarity.`sims` the sub-similarities used to create the combined score

    Methods in org.apache.lucene.search.similarities that return Similarity
    Modifier and Type | Method and Description
    --- | ---
    `abstract Similarity` | PerFieldSimilarityWrapper.`get(String name)` Returns a `Similarity` for scoring a field.

    Constructors in org.apache.lucene.search.similarities with parameters of type Similarity
    Constructor and Description
    `MultiSimilarity(Similarity[] sims)` Creates a MultiSimilarity which will sum the scores of the provided `sims`.
    `PerFieldSimilarityWrapper(Similarity defaultSim)` Constructor taking a default similarity for all non-field specific calculations.

  - ### Uses of Similarity in org.apache.lucene.search.spans

    Fields in org.apache.lucene.search.spans declared as Similarity
    Modifier and Type | Field and Description
    --- | ---
    `protected Similarity` | SpanWeight.`similarity`

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