mirror of https://github.com/apache/lucene.git
LUCENE-5284 - added method for training with a Query filter
git-svn-id: https://svn.apache.org/repos/asf/lucene/dev/trunk@1532983 13f79535-47bb-0310-9956-ffa450edef68
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@ -16,12 +16,6 @@
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*/
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package org.apache.lucene.classification;
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import java.io.IOException;
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import java.io.StringReader;
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import java.util.Map;
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import java.util.SortedMap;
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import java.util.TreeMap;
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import org.apache.lucene.analysis.Analyzer;
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import org.apache.lucene.analysis.TokenStream;
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import org.apache.lucene.analysis.tokenattributes.CharTermAttribute;
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@ -33,6 +27,7 @@ import org.apache.lucene.index.Terms;
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import org.apache.lucene.index.TermsEnum;
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import org.apache.lucene.search.IndexSearcher;
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import org.apache.lucene.search.MatchAllDocsQuery;
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import org.apache.lucene.search.Query;
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import org.apache.lucene.search.ScoreDoc;
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import org.apache.lucene.util.BytesRef;
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import org.apache.lucene.util.IntsRef;
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@ -41,6 +36,11 @@ import org.apache.lucene.util.fst.FST;
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import org.apache.lucene.util.fst.PositiveIntOutputs;
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import org.apache.lucene.util.fst.Util;
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import java.io.IOException;
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import java.util.Map;
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import java.util.SortedMap;
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import java.util.TreeMap;
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/**
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* A perceptron (see <code>http://en.wikipedia.org/wiki/Perceptron</code>) based
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* <code>Boolean</code> {@link org.apache.lucene.classification.Classifier}. The
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@ -113,7 +113,16 @@ public class BooleanPerceptronClassifier implements Classifier<Boolean> {
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*/
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@Override
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public void train(AtomicReader atomicReader, String textFieldName,
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String classFieldName, Analyzer analyzer) throws IOException {
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String classFieldName, Analyzer analyzer) throws IOException {
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train(atomicReader, textFieldName, classFieldName, analyzer, null);
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}
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/**
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* {@inheritDoc}
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*/
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@Override
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public void train(AtomicReader atomicReader, String textFieldName,
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String classFieldName, Analyzer analyzer, Query query) throws IOException {
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this.textTerms = MultiFields.getTerms(atomicReader, textFieldName);
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if (textTerms == null) {
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@ -151,8 +160,15 @@ public class BooleanPerceptronClassifier implements Classifier<Boolean> {
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int batchCount = 0;
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Query q;
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if (query != null) {
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q = query;
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}
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else {
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q = new MatchAllDocsQuery();
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}
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// do a *:* search and use stored field values
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for (ScoreDoc scoreDoc : indexSearcher.search(new MatchAllDocsQuery(),
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for (ScoreDoc scoreDoc : indexSearcher.search(q,
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Integer.MAX_VALUE).scoreDocs) {
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StoredDocument doc = indexSearcher.doc(scoreDoc.doc);
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@ -18,6 +18,7 @@ package org.apache.lucene.classification;
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import org.apache.lucene.analysis.Analyzer;
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import org.apache.lucene.index.AtomicReader;
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import org.apache.lucene.search.Query;
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import java.io.IOException;
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@ -47,4 +48,16 @@ public interface Classifier<T> {
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public void train(AtomicReader atomicReader, String textFieldName, String classFieldName, Analyzer analyzer)
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throws IOException;
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/**
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* Train the classifier using the underlying Lucene index
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* @param atomicReader the reader to use to access the Lucene index
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* @param textFieldName the name of the field used to compare documents
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* @param classFieldName the name of the field containing the class assigned to documents
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* @param analyzer the analyzer used to tokenize / filter the unseen text
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* @param query the query to filter which documents use for training
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* @throws IOException If there is a low-level I/O error.
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*/
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public void train(AtomicReader atomicReader, String textFieldName, String classFieldName, Analyzer analyzer, Query query)
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throws IOException;
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}
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@ -19,6 +19,8 @@ package org.apache.lucene.classification;
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import org.apache.lucene.analysis.Analyzer;
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import org.apache.lucene.index.AtomicReader;
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import org.apache.lucene.queries.mlt.MoreLikeThis;
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import org.apache.lucene.search.BooleanClause;
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import org.apache.lucene.search.BooleanQuery;
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import org.apache.lucene.search.IndexSearcher;
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import org.apache.lucene.search.Query;
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import org.apache.lucene.search.ScoreDoc;
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@ -43,6 +45,7 @@ public class KNearestNeighborClassifier implements Classifier<BytesRef> {
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private String classFieldName;
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private IndexSearcher indexSearcher;
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private int k;
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private Query query;
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/**
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* Create a {@link Classifier} using kNN algorithm
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@ -61,7 +64,16 @@ public class KNearestNeighborClassifier implements Classifier<BytesRef> {
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if (mlt == null) {
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throw new IOException("You must first call Classifier#train");
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}
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Query q = mlt.like(new StringReader(text), textFieldName);
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Query q;
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if (query != null) {
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Query mltQuery = mlt.like(new StringReader(text), textFieldName);
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BooleanQuery bq = new BooleanQuery();
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bq.add(query, BooleanClause.Occur.MUST);
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bq.add(mltQuery, BooleanClause.Occur.MUST);
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q = bq;
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} else {
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q = mlt.like(new StringReader(text), textFieldName);
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}
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TopDocs topDocs = indexSearcher.search(q, k);
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return selectClassFromNeighbors(topDocs);
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}
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@ -96,11 +108,20 @@ public class KNearestNeighborClassifier implements Classifier<BytesRef> {
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*/
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@Override
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public void train(AtomicReader atomicReader, String textFieldName, String classFieldName, Analyzer analyzer) throws IOException {
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train(atomicReader, textFieldName, classFieldName, analyzer, null);
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}
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/**
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* {@inheritDoc}
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*/
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@Override
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public void train(AtomicReader atomicReader, String textFieldName, String classFieldName, Analyzer analyzer, Query query) throws IOException {
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this.textFieldName = textFieldName;
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this.classFieldName = classFieldName;
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mlt = new MoreLikeThis(atomicReader);
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mlt.setAnalyzer(analyzer);
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mlt.setFieldNames(new String[]{textFieldName});
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indexSearcher = new IndexSearcher(atomicReader);
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this.query = query;
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}
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}
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@ -27,6 +27,7 @@ import org.apache.lucene.index.TermsEnum;
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import org.apache.lucene.search.BooleanClause;
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import org.apache.lucene.search.BooleanQuery;
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import org.apache.lucene.search.IndexSearcher;
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import org.apache.lucene.search.Query;
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import org.apache.lucene.search.TermQuery;
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import org.apache.lucene.search.TotalHitCountCollector;
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import org.apache.lucene.search.WildcardQuery;
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@ -49,6 +50,7 @@ public class SimpleNaiveBayesClassifier implements Classifier<BytesRef> {
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private int docsWithClassSize;
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private Analyzer analyzer;
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private IndexSearcher indexSearcher;
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private Query query;
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/**
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* Creates a new NaiveBayes classifier.
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@ -62,7 +64,7 @@ public class SimpleNaiveBayesClassifier implements Classifier<BytesRef> {
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* {@inheritDoc}
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*/
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@Override
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public void train(AtomicReader atomicReader, String textFieldName, String classFieldName, Analyzer analyzer)
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public void train(AtomicReader atomicReader, String textFieldName, String classFieldName, Analyzer analyzer, Query query)
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throws IOException {
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this.atomicReader = atomicReader;
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this.indexSearcher = new IndexSearcher(this.atomicReader);
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@ -70,13 +72,29 @@ public class SimpleNaiveBayesClassifier implements Classifier<BytesRef> {
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this.classFieldName = classFieldName;
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this.analyzer = analyzer;
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this.docsWithClassSize = countDocsWithClass();
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this.query = query;
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}
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@Override
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public void train(AtomicReader atomicReader, String textFieldName, String classFieldName, Analyzer analyzer) throws IOException {
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train(atomicReader, textFieldName, classFieldName, analyzer, null);
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}
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private int countDocsWithClass() throws IOException {
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int docCount = MultiFields.getTerms(this.atomicReader, this.classFieldName).getDocCount();
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if (docCount == -1) { // in case codec doesn't support getDocCount
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TotalHitCountCollector totalHitCountCollector = new TotalHitCountCollector();
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indexSearcher.search(new WildcardQuery(new Term(classFieldName, String.valueOf(WildcardQuery.WILDCARD_STRING))),
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Query q;
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if (query != null) {
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BooleanQuery bq = new BooleanQuery();
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WildcardQuery wq = new WildcardQuery(new Term(classFieldName, String.valueOf(WildcardQuery.WILDCARD_STRING)));
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bq.add(wq, BooleanClause.Occur.MUST);
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bq.add(query, BooleanClause.Occur.MUST);
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q = bq;
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} else {
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q = new WildcardQuery(new Term(classFieldName, String.valueOf(WildcardQuery.WILDCARD_STRING)));
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}
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indexSearcher.search(q,
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totalHitCountCollector);
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docCount = totalHitCountCollector.getTotalHits();
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}
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@ -157,6 +175,9 @@ public class SimpleNaiveBayesClassifier implements Classifier<BytesRef> {
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BooleanQuery booleanQuery = new BooleanQuery();
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booleanQuery.add(new BooleanClause(new TermQuery(new Term(textFieldName, word)), BooleanClause.Occur.MUST));
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booleanQuery.add(new BooleanClause(new TermQuery(new Term(classFieldName, c)), BooleanClause.Occur.MUST));
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if (query != null) {
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booleanQuery.add(query, BooleanClause.Occur.MUST);
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}
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TotalHitCountCollector totalHitCountCollector = new TotalHitCountCollector();
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indexSearcher.search(booleanQuery, totalHitCountCollector);
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return totalHitCountCollector.getTotalHits();
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@ -17,6 +17,8 @@
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package org.apache.lucene.classification;
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import org.apache.lucene.analysis.MockAnalyzer;
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import org.apache.lucene.index.Term;
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import org.apache.lucene.search.TermQuery;
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import org.junit.Test;
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/**
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@ -34,6 +36,11 @@ public class BooleanPerceptronClassifierTest extends ClassificationTestBase<Bool
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checkCorrectClassification(new BooleanPerceptronClassifier(100d, 1), TECHNOLOGY_INPUT, false, new MockAnalyzer(random()), textFieldName, booleanFieldName);
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}
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@Test
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public void testBasicUsageWithQuery() throws Exception {
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checkCorrectClassification(new BooleanPerceptronClassifier(), TECHNOLOGY_INPUT, false, new MockAnalyzer(random()), textFieldName, booleanFieldName, new TermQuery(new Term(textFieldName, "it")));
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}
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@Test
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public void testPerformance() throws Exception {
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checkPerformance(new BooleanPerceptronClassifier(), new MockAnalyzer(random()), booleanFieldName);
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@ -24,6 +24,7 @@ import org.apache.lucene.document.TextField;
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import org.apache.lucene.index.AtomicReader;
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import org.apache.lucene.index.RandomIndexWriter;
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import org.apache.lucene.index.SlowCompositeReaderWrapper;
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import org.apache.lucene.search.Query;
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import org.apache.lucene.store.Directory;
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import org.apache.lucene.util.BytesRef;
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import org.apache.lucene.util.LuceneTestCase;
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@ -70,13 +71,16 @@ public abstract class ClassificationTestBase<T> extends LuceneTestCase {
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dir.close();
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}
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protected void checkCorrectClassification(Classifier<T> classifier, String inputDoc, T expectedResult, Analyzer analyzer, String textFieldName, String classFieldName) throws Exception {
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checkCorrectClassification(classifier, inputDoc, expectedResult, analyzer, textFieldName, classFieldName, null);
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}
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protected void checkCorrectClassification(Classifier<T> classifier, String inputDoc, T expectedResult, Analyzer analyzer, String textFieldName, String classFieldName, Query query) throws Exception {
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AtomicReader atomicReader = null;
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try {
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populateSampleIndex(analyzer);
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atomicReader = SlowCompositeReaderWrapper.wrap(indexWriter.getReader());
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classifier.train(atomicReader, textFieldName, classFieldName, analyzer);
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classifier.train(atomicReader, textFieldName, classFieldName, analyzer, query);
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ClassificationResult<T> classificationResult = classifier.assignClass(inputDoc);
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assertNotNull(classificationResult.getAssignedClass());
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assertEquals("got an assigned class of " + classificationResult.getAssignedClass(), expectedResult, classificationResult.getAssignedClass());
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@ -17,6 +17,8 @@
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package org.apache.lucene.classification;
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import org.apache.lucene.analysis.MockAnalyzer;
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import org.apache.lucene.index.Term;
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import org.apache.lucene.search.TermQuery;
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import org.apache.lucene.util.BytesRef;
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import org.junit.Test;
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@ -30,6 +32,11 @@ public class KNearestNeighborClassifierTest extends ClassificationTestBase<Bytes
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checkCorrectClassification(new KNearestNeighborClassifier(1), TECHNOLOGY_INPUT, TECHNOLOGY_RESULT, new MockAnalyzer(random()), textFieldName, categoryFieldName);
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}
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@Test
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public void testBasicUsageWithQuery() throws Exception {
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checkCorrectClassification(new KNearestNeighborClassifier(1), TECHNOLOGY_INPUT, TECHNOLOGY_RESULT, new MockAnalyzer(random()), textFieldName, categoryFieldName, new TermQuery(new Term(textFieldName, "it")));
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}
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@Test
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public void testPerformance() throws Exception {
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checkPerformance(new KNearestNeighborClassifier(100), new MockAnalyzer(random()), categoryFieldName);
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@ -22,6 +22,8 @@ import org.apache.lucene.analysis.Tokenizer;
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import org.apache.lucene.analysis.core.KeywordTokenizer;
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import org.apache.lucene.analysis.ngram.EdgeNGramTokenFilter;
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import org.apache.lucene.analysis.reverse.ReverseStringFilter;
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import org.apache.lucene.index.Term;
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import org.apache.lucene.search.TermQuery;
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import org.apache.lucene.util.BytesRef;
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import org.apache.lucene.util.LuceneTestCase;
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import org.junit.Test;
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checkCorrectClassification(new SimpleNaiveBayesClassifier(), POLITICS_INPUT, POLITICS_RESULT, new MockAnalyzer(random()), textFieldName, categoryFieldName);
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}
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@Test
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public void testBasicUsageWithQuery() throws Exception {
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checkCorrectClassification(new SimpleNaiveBayesClassifier(), TECHNOLOGY_INPUT, TECHNOLOGY_RESULT, new MockAnalyzer(random()), textFieldName, categoryFieldName, new TermQuery(new Term(textFieldName, "it")));
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}
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@Test
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public void testNGramUsage() throws Exception {
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checkCorrectClassification(new SimpleNaiveBayesClassifier(), TECHNOLOGY_INPUT, TECHNOLOGY_RESULT, new NGramAnalyzer(), textFieldName, categoryFieldName);
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