Module org.elasticsearch.server
Class JLHScore
java.lang.Object
org.elasticsearch.search.aggregations.bucket.terms.heuristic.SignificanceHeuristic
org.elasticsearch.search.aggregations.bucket.terms.heuristic.JLHScore
- All Implemented Interfaces:
NamedWriteable
,Writeable
,ToXContent
,ToXContentFragment
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Nested Class Summary
Nested classes/interfaces inherited from interface org.elasticsearch.xcontent.ToXContent
ToXContent.DelegatingMapParams, ToXContent.MapParams, ToXContent.Params
Nested classes/interfaces inherited from interface org.elasticsearch.common.io.stream.Writeable
Writeable.Reader<V>, Writeable.Writer<V>
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Field Summary
Fields inherited from interface org.elasticsearch.xcontent.ToXContent
EMPTY, EMPTY_PARAMS
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Constructor Summary
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Method Summary
Modifier and TypeMethodDescriptionboolean
double
getScore
(long subsetFreq, long subsetSize, long supersetFreq, long supersetSize) Calculates the significance of a term in a sample against a background of normal distributions by comparing the changes in frequency.Returns the name of the writeable objectint
hashCode()
toXContent
(XContentBuilder builder, ToXContent.Params params) void
writeTo
(StreamOutput out) Write this into the StreamOutput.Methods inherited from class org.elasticsearch.search.aggregations.bucket.terms.heuristic.SignificanceHeuristic
checkFrequencyValidity, rewrite, rewrite
Methods inherited from class java.lang.Object
clone, finalize, getClass, notify, notifyAll, toString, wait, wait, wait
Methods inherited from interface org.elasticsearch.xcontent.ToXContentFragment
isFragment
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Field Details
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NAME
- See Also:
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PARSER
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Constructor Details
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JLHScore
public JLHScore() -
JLHScore
Read from a stream.
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Method Details
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writeTo
Description copied from interface:Writeable
Write this into the StreamOutput.- Throws:
IOException
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getWriteableName
Description copied from interface:NamedWriteable
Returns the name of the writeable object -
getScore
public double getScore(long subsetFreq, long subsetSize, long supersetFreq, long supersetSize) Calculates the significance of a term in a sample against a background of normal distributions by comparing the changes in frequency. This is the heart of the significant terms feature.- Specified by:
getScore
in classSignificanceHeuristic
- Parameters:
subsetFreq
- The frequency of the term in the selected samplesubsetSize
- The size of the selected sample (typically number of docs)supersetFreq
- The frequency of the term in the superset from which the sample was takensupersetSize
- The size of the superset from which the sample was taken (typically number of docs)- Returns:
- a "significance" score
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toXContent
public XContentBuilder toXContent(XContentBuilder builder, ToXContent.Params params) throws IOException - Throws:
IOException
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equals
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hashCode
public int hashCode()
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