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

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

Uses of BasicStats in org.apache.lucene.search.similarities

Subclasses of BasicStats in org.apache.lucene.search.similarities
`static class` `LMSimilarity.LMStats` Stores the collection distribution of the current term.

Methods in org.apache.lucene.search.similarities that return BasicStats
`protected BasicStats` `SimilarityBase.newStats(String field, float queryBoost)` Factory method to return a custom stats object
`protected BasicStats` `LMSimilarity.newStats(String field, float queryBoost)`

Methods in org.apache.lucene.search.similarities with parameters of type BasicStats
`float` `LMSimilarity.CollectionModel.computeProbability(BasicStats stats)` Computes the probability `p(w|C)` according to the language model strategy for the current term.
`float` `LMSimilarity.DefaultCollectionModel.computeProbability(BasicStats stats)`
`abstract Explanation` `Lambda.explain(BasicStats stats)` Explains the lambda parameter.
`Explanation` `LambdaTTF.explain(BasicStats stats)`
`Explanation` `LambdaDF.explain(BasicStats stats)`
`abstract Explanation` `AfterEffect.explain(BasicStats stats, float tfn)` Returns an explanation for the score.
`Explanation` `AfterEffect.NoAfterEffect.explain(BasicStats stats, float tfn)`
`Explanation` `AfterEffectB.explain(BasicStats stats, float tfn)`
`Explanation` `AfterEffectL.explain(BasicStats stats, float tfn)`
`Explanation` `BasicModel.explain(BasicStats stats, float tfn)` Returns an explanation for the score.
`Explanation` `BasicModelIn.explain(BasicStats stats, float tfn)`
`Explanation` `Distribution.explain(BasicStats stats, float tfn, float lambda)` Explains the score.
`Explanation` `Normalization.explain(BasicStats stats, float tf, float len)` Returns an explanation for the normalized term frequency.
`Explanation` `Normalization.NoNormalization.explain(BasicStats stats, float tf, float len)`
`protected Explanation` `SimilarityBase.explain(BasicStats stats, int doc, Explanation freq, float docLen)` Explains the score.
`protected void` `SimilarityBase.explain(Explanation expl, BasicStats stats, int doc, float freq, float docLen)` Subclasses should implement this method to explain the score.
`protected void` `LMDirichletSimilarity.explain(Explanation expl, BasicStats stats, int doc, float freq, float docLen)`
`protected void` `DFRSimilarity.explain(Explanation expl, BasicStats stats, int doc, float freq, float docLen)`
`protected void` `IBSimilarity.explain(Explanation expl, BasicStats stats, int doc, float freq, float docLen)`
`protected void` `LMSimilarity.explain(Explanation expl, BasicStats stats, int doc, float freq, float docLen)`
`protected void` `LMJelinekMercerSimilarity.explain(Explanation expl, BasicStats stats, int doc, float freq, float docLen)`
`protected void` `SimilarityBase.fillBasicStats(BasicStats stats, CollectionStatistics collectionStats, TermStatistics termStats)` Fills all member fields defined in `BasicStats` in `stats`.
`protected void` `LMSimilarity.fillBasicStats(BasicStats stats, CollectionStatistics collectionStats, TermStatistics termStats)` Computes the collection probability of the current term in addition to the usual statistics.
`abstract float` `Lambda.lambda(BasicStats stats)` Computes the lambda parameter.
`float` `LambdaTTF.lambda(BasicStats stats)`
`float` `LambdaDF.lambda(BasicStats stats)`
`float` `BasicModelIF.score(BasicStats stats, float tfn)`
`float` `BasicModelD.score(BasicStats stats, float tfn)`
`float` `BasicModelBE.score(BasicStats stats, float tfn)`
`float` `BasicModelG.score(BasicStats stats, float tfn)`
`abstract float` `AfterEffect.score(BasicStats stats, float tfn)` Returns the aftereffect score.
`float` `AfterEffect.NoAfterEffect.score(BasicStats stats, float tfn)`
`float` `BasicModelP.score(BasicStats stats, float tfn)`
`float` `AfterEffectB.score(BasicStats stats, float tfn)`
`float` `AfterEffectL.score(BasicStats stats, float tfn)`
`abstract float` `BasicModel.score(BasicStats stats, float tfn)` Returns the informative content score.
`float` `BasicModelIn.score(BasicStats stats, float tfn)`
`float` `BasicModelIne.score(BasicStats stats, float tfn)`
`abstract float` `Distribution.score(BasicStats stats, float tfn, float lambda)` Computes the score.
`protected abstract float` `SimilarityBase.score(BasicStats stats, float freq, float docLen)` Scores the document `doc`.
`protected float` `LMDirichletSimilarity.score(BasicStats stats, float freq, float docLen)`
`float` `DistributionLL.score(BasicStats stats, float tfn, float lambda)`
`float` `DistributionSPL.score(BasicStats stats, float tfn, float lambda)`
`protected float` `DFRSimilarity.score(BasicStats stats, float freq, float docLen)`
`protected float` `IBSimilarity.score(BasicStats stats, float freq, float docLen)`
`protected float` `LMJelinekMercerSimilarity.score(BasicStats stats, float freq, float docLen)`
`abstract float` `Normalization.tfn(BasicStats stats, float tf, float len)` Returns the normalized term frequency.
`float` `Normalization.NoNormalization.tfn(BasicStats stats, float tf, float len)`
`float` `NormalizationZ.tfn(BasicStats stats, float tf, float len)`
`float` `NormalizationH3.tfn(BasicStats stats, float tf, float len)`
`float` `NormalizationH1.tfn(BasicStats stats, float tf, float len)`
`float` `NormalizationH2.tfn(BasicStats stats, float tf, float len)`

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