Package org.apache.lucene.classification
Class BM25NBClassifier
java.lang.Object
org.apache.lucene.classification.BM25NBClassifier
- All Implemented Interfaces:
Classifier<BytesRef>
A classifier approximating naive bayes classifier by using pure queries on BM25.
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Field Summary
FieldsModifier and TypeFieldDescriptionprivate final AnalyzerAnalyzerto be used for tokenizing unseen input textprivate final Stringname of the field to be used as a class / category outputprivate final IndexReaderIndexReaderused to access theClassifier's indexprivate final IndexSearcherIndexSearcherto run searches on the index for retrieving frequenciesprivate final QueryQueryused to eventually filter the document set to be used to classifyprivate final String[]names of the fields to be used as input text -
Constructor Summary
ConstructorsConstructorDescriptionBM25NBClassifier(IndexReader indexReader, Analyzer analyzer, Query query, String classFieldName, String... textFieldNames) Creates a new NaiveBayes classifier. -
Method Summary
Modifier and TypeMethodDescriptionassignClass(String inputDocument) Assign a class (with score) to the given text Stringprivate List<ClassificationResult<BytesRef>> assignClassNormalizedList(String inputDocument) Calculate probabilities for all classes for a given input textprivate doublecalculateLogLikelihood(String[] tokens, Term term) private doublecalculateLogPrior(Term term) getClasses(String text) Get all the classes (sorted by score, descending) assigned to the given text String.getClasses(String text, int max) Get the firstmaxclasses (sorted by score, descending) assigned to the given text String.private doublegetTermProbForClass(Term classTerm, String... words) private ArrayList<ClassificationResult<BytesRef>> normClassificationResults(List<ClassificationResult<BytesRef>> assignedClasses) Normalize the classification results based on the max score availableprivate String[]tokenize aStringon this classifier's text fields and analyzer
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Field Details
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indexReader
IndexReaderused to access theClassifier's index -
textFieldNames
names of the fields to be used as input text -
classFieldName
name of the field to be used as a class / category output -
analyzer
Analyzerto be used for tokenizing unseen input text -
indexSearcher
IndexSearcherto run searches on the index for retrieving frequencies -
query
Queryused to eventually filter the document set to be used to classify
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Constructor Details
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BM25NBClassifier
public BM25NBClassifier(IndexReader indexReader, Analyzer analyzer, Query query, String classFieldName, String... textFieldNames) Creates a new NaiveBayes classifier.- Parameters:
indexReader- the reader on the index to be used for classificationanalyzer- anAnalyzerused to analyze unseen textquery- aQueryto eventually filter the docs used for training the classifier, ornullif all the indexed docs should be usedclassFieldName- the name of the field used as the output for the classifier NOTE: must not be heavely analyzed as the returned class will be a token indexed for this fieldtextFieldNames- the name of the fields used as the inputs for the classifier, NO boosting supported per field
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Method Details
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assignClass
Description copied from interface:ClassifierAssign a class (with score) to the given text String- Specified by:
assignClassin interfaceClassifier<BytesRef>- Parameters:
inputDocument- a String containing text to be classified- Returns:
- a
ClassificationResultholding assigned class of typeTand score - Throws:
IOException- If there is a low-level I/O error.
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getClasses
Description copied from interface:ClassifierGet all the classes (sorted by score, descending) assigned to the given text String.- Specified by:
getClassesin interfaceClassifier<BytesRef>- Parameters:
text- a String containing text to be classified- Returns:
- the whole list of
ClassificationResult, the classes and scores. Returnsnullif the classifier can't make lists. - Throws:
IOException- If there is a low-level I/O error.
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getClasses
Description copied from interface:ClassifierGet the firstmaxclasses (sorted by score, descending) assigned to the given text String.- Specified by:
getClassesin interfaceClassifier<BytesRef>- Parameters:
text- a String containing text to be classifiedmax- the number of return list elements- Returns:
- the whole list of
ClassificationResult, the classes and scores. Cut for "max" number of elements. Returnsnullif the classifier can't make lists. - Throws:
IOException- If there is a low-level I/O error.
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assignClassNormalizedList
private List<ClassificationResult<BytesRef>> assignClassNormalizedList(String inputDocument) throws IOException Calculate probabilities for all classes for a given input text- Parameters:
inputDocument- the input text as aString- Returns:
- a
ListofClassificationResult, one for each existing class - Throws:
IOException- if assigning probabilities fails
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normClassificationResults
private ArrayList<ClassificationResult<BytesRef>> normClassificationResults(List<ClassificationResult<BytesRef>> assignedClasses) Normalize the classification results based on the max score available- Parameters:
assignedClasses- the list of assigned classes- Returns:
- the normalized results
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tokenize
tokenize aStringon this classifier's text fields and analyzer- Parameters:
text- theStringrepresenting an input text (to be classified)- Returns:
- a
Stringarray of the resulting tokens - Throws:
IOException- if tokenization fails
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calculateLogLikelihood
- Throws:
IOException
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getTermProbForClass
- Throws:
IOException
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calculateLogPrior
- Throws:
IOException
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