Class SimpleNaiveBayesDocumentClassifier
java.lang.Object
org.apache.lucene.classification.SimpleNaiveBayesClassifier
org.apache.lucene.classification.document.SimpleNaiveBayesDocumentClassifier
- All Implemented Interfaces:
Classifier<BytesRef>,DocumentClassifier<BytesRef>
public class SimpleNaiveBayesDocumentClassifier
extends SimpleNaiveBayesClassifier
implements DocumentClassifier<BytesRef>
A simplistic Lucene based NaiveBayes classifier, see
http://en.wikipedia.org/wiki/Naive_Bayes_classifier-
Field Summary
FieldsFields inherited from class org.apache.lucene.classification.SimpleNaiveBayesClassifier
analyzer, classFieldName, indexReader, indexSearcher, query, textFieldNames -
Constructor Summary
ConstructorsConstructorDescriptionSimpleNaiveBayesDocumentClassifier(IndexReader indexReader, Query query, String classFieldName, Map<String, Analyzer> field2analyzer, String... textFieldNames) Creates a new NaiveBayes classifier. -
Method Summary
Modifier and TypeMethodDescriptionprivate voidanalyzeSeedDocument(Document inputDocument, Map<String, List<String[]>> fieldName2tokensArray, Map<String, Float> fieldName2boost) This methods performs the analysis for the seed document and extract the boosts if present.assignClass(Document document) Assign a class (with score) to the givenDocumentprivate List<ClassificationResult<BytesRef>> assignNormClasses(Document inputDocument) private doublecalculateLogLikelihood(String[] tokenizedText, String fieldName, Term term, int docsWithClass) private doublecalculateLogPrior(Term term, int docsWithClassSize) private intgetClasses(Document document) Get all the classes (sorted by score, descending) assigned to the givenDocument.getClasses(Document document, int max) Get the firstmaxclasses (sorted by score, descending) assigned to the given text String.private doublegetTextTermFreqForClass(Term term, String fieldName) Returns the average number of unique terms times the number of docs belonging to the input classprotected String[]getTokenArray(TokenStream tokenizedText) Returns a token array from theTokenStreamin inputprivate intgetWordFreqForClass(String word, String fieldName, Term term) Returns the number of documents of the input class ( from the whole index or from a subset) that contains the word ( in a specific field or in all the fields if no one selected)Methods inherited from class org.apache.lucene.classification.SimpleNaiveBayesClassifier
assignClass, assignClassNormalizedList, countDocsWithClass, getClasses, getClasses, normClassificationResults, tokenize
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Field Details
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field2analyzer
Analyzerto be used for tokenizing document fields
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Constructor Details
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SimpleNaiveBayesDocumentClassifier
public SimpleNaiveBayesDocumentClassifier(IndexReader indexReader, Query query, String classFieldName, Map<String, Analyzer> field2analyzer, String... textFieldNames) Creates a new NaiveBayes classifier.- Parameters:
indexReader- the reader on the index to be used for classificationquery- 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, they can contain boosting indication e.g. title^10
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Method Details
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assignClass
Description copied from interface:DocumentClassifierAssign a class (with score) to the givenDocument- Specified by:
assignClassin interfaceDocumentClassifier<BytesRef>- Parameters:
document- aDocumentto be classified. Fields are considered features for the classification.- 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:DocumentClassifierGet all the classes (sorted by score, descending) assigned to the givenDocument.- Specified by:
getClassesin interfaceDocumentClassifier<BytesRef>- Parameters:
document- aDocumentto be classified. Fields are considered features for the classification.- 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
public List<ClassificationResult<BytesRef>> getClasses(Document document, int max) throws IOException Description copied from interface:DocumentClassifierGet the firstmaxclasses (sorted by score, descending) assigned to the given text String.- Specified by:
getClassesin interfaceDocumentClassifier<BytesRef>- Parameters:
document- aDocumentto be classified. Fields are considered features for the classification.max- 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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assignNormClasses
private List<ClassificationResult<BytesRef>> assignNormClasses(Document inputDocument) throws IOException - Throws:
IOException
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analyzeSeedDocument
private void analyzeSeedDocument(Document inputDocument, Map<String, List<String[]>> fieldName2tokensArray, Map<String, throws IOExceptionFloat> fieldName2boost) This methods performs the analysis for the seed document and extract the boosts if present. This is done only one time for the Seed Document.- Parameters:
inputDocument- the seed unseen documentfieldName2tokensArray- a map that associated to a field name the list of token arrays for all its valuesfieldName2boost- a map that associates the boost to the field- Throws:
IOException- If there is a low-level I/O error
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getTokenArray
Returns a token array from theTokenStreamin input- Parameters:
tokenizedText- the tokenized content of a field- Returns:
- a
Stringarray of the resulting tokens - Throws:
IOException- If tokenization fails because there is a low-level I/O error
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calculateLogLikelihood
private double calculateLogLikelihood(String[] tokenizedText, String fieldName, Term term, int docsWithClass) throws IOException - Parameters:
tokenizedText- the tokenized content of a fieldfieldName- the input field nameterm- theTermreferring to the class to calculate the score ofdocsWithClass- the total number of docs that have a class- Returns:
- a normalized score for the class
- Throws:
IOException- If there is a low-level I/O error
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getTextTermFreqForClass
Returns the average number of unique terms times the number of docs belonging to the input class- Parameters:
term- the class term- Returns:
- the average number of unique terms
- Throws:
IOException- If there is a low-level I/O error
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getWordFreqForClass
Returns the number of documents of the input class ( from the whole index or from a subset) that contains the word ( in a specific field or in all the fields if no one selected)- Parameters:
word- the token produced by the analyzerfieldName- the field the word is coming fromterm- the class term- Returns:
- number of documents of the input class
- Throws:
IOException- If there is a low-level I/O error
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calculateLogPrior
- Throws:
IOException
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docCount
- Throws:
IOException
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