Examples with Feature org.apache.solr.ltr.feature.Feature used on opensource projects

Example 16 with Feature

use of org.apache.solr.ltr.feature.Feature in project lucene-solr by apache.

the class TestSelectiveWeightCreation method makeFeatureWeights.

private static Map<String, Object> makeFeatureWeights(List<Feature> features) {
    final Map<String, Object> nameParams = new HashMap<String, Object>();
    final HashMap<String, Double> modelWeights = new HashMap<String, Double>();
    for (final Feature feat : features) {
        modelWeights.put(feat.getName(), 0.1);
    }
    nameParams.put("weights", modelWeights);
    return nameParams;
}

Example 17 with Feature

use of org.apache.solr.ltr.feature.Feature in project lucene-solr by apache.

the class TestSelectiveWeightCreation method makeFeatures.

private static List<Feature> makeFeatures(int[] featureIds) {
    final List<Feature> features = new ArrayList<>();
    for (final int i : featureIds) {
        Map<String, Object> params = new HashMap<String, Object>();
        params.put("value", i);
        final Feature f = Feature.getInstance(solrResourceLoader, ValueFeature.class.getCanonicalName(), "f" + i, params);
        f.setIndex(i);
        features.add(f);
    }
    return features;
}

Example 18 with Feature

use of org.apache.solr.ltr.feature.Feature in project lucene-solr by apache.

the class TestSelectiveWeightCreation method testScoringQueryWeightCreation.

@Test
public void testScoringQueryWeightCreation() throws IOException, ModelException {
    final Directory dir = newDirectory();
    final RandomIndexWriter w = new RandomIndexWriter(random(), dir);
    Document doc = new Document();
    doc.add(newStringField("id", "10", Field.Store.YES));
    doc.add(newTextField("field", "wizard the the the the the oz", Field.Store.NO));
    doc.add(new FloatDocValuesField("final-score", 1.0f));
    w.addDocument(doc);
    doc = new Document();
    doc.add(newStringField("id", "11", Field.Store.YES));
    // 1 extra token, but wizard and oz are close;
    doc.add(newTextField("field", "wizard oz the the the the the the", Field.Store.NO));
    doc.add(new FloatDocValuesField("final-score", 2.0f));
    w.addDocument(doc);
    final IndexReader r = w.getReader();
    w.close();
    // Do ordinary BooleanQuery:
    final BooleanQuery.Builder bqBuilder = new BooleanQuery.Builder();
    bqBuilder.add(new TermQuery(new Term("field", "wizard")), BooleanClause.Occur.SHOULD);
    bqBuilder.add(new TermQuery(new Term("field", "oz")), BooleanClause.Occur.SHOULD);
    final IndexSearcher searcher = getSearcher(r);
    // first run the standard query
    final TopDocs hits = searcher.search(bqBuilder.build(), 10);
    assertEquals(2, hits.totalHits);
    assertEquals("10", searcher.doc(hits.scoreDocs[0].doc).get("id"));
    assertEquals("11", searcher.doc(hits.scoreDocs[1].doc).get("id"));
    List<Feature> features = makeFeatures(new int[] { 0, 1, 2 });
    final List<Feature> allFeatures = makeFeatures(new int[] { 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 });
    final List<Normalizer> norms = new ArrayList<>();
    for (int k = 0; k < features.size(); ++k) {
        norms.add(IdentityNormalizer.INSTANCE);
    }
    // when features are NOT requested in the response, only the modelFeature weights should be created
    final LTRScoringModel ltrScoringModel1 = TestLinearModel.createLinearModel("test", features, norms, "test", allFeatures, makeFeatureWeights(features));
    LTRScoringQuery.ModelWeight modelWeight = performQuery(hits, searcher, hits.scoreDocs[0].doc, // features not requested in response
    new LTRScoringQuery(ltrScoringModel1, false));
    LTRScoringQuery.FeatureInfo[] featuresInfo = modelWeight.getFeaturesInfo();
    assertEquals(features.size(), modelWeight.getModelFeatureValuesNormalized().length);
    int validFeatures = 0;
    for (int i = 0; i < featuresInfo.length; ++i) {
        if (featuresInfo[i] != null && featuresInfo[i].isUsed()) {
            validFeatures += 1;
        }
    }
    assertEquals(validFeatures, features.size());
    // when features are requested in the response, weights should be created for all features
    final LTRScoringModel ltrScoringModel2 = TestLinearModel.createLinearModel("test", features, norms, "test", allFeatures, makeFeatureWeights(features));
    modelWeight = performQuery(hits, searcher, hits.scoreDocs[0].doc, // features requested in response
    new LTRScoringQuery(ltrScoringModel2, true));
    featuresInfo = modelWeight.getFeaturesInfo();
    assertEquals(features.size(), modelWeight.getModelFeatureValuesNormalized().length);
    assertEquals(allFeatures.size(), modelWeight.getExtractedFeatureWeights().length);
    validFeatures = 0;
    for (int i = 0; i < featuresInfo.length; ++i) {
        if (featuresInfo[i] != null && featuresInfo[i].isUsed()) {
            validFeatures += 1;
        }
    }
    assertEquals(validFeatures, allFeatures.size());
    assertU(delI("10"));
    assertU(delI("11"));
    r.close();
    dir.close();
}

Example 19 with Feature

use of org.apache.solr.ltr.feature.Feature in project lucene-solr by apache.

the class TestLTRReRankingPipeline method testRescorer.

@Ignore
@Test
public void testRescorer() throws IOException {
    final Directory dir = newDirectory();
    final RandomIndexWriter w = new RandomIndexWriter(random(), dir);
    Document doc = new Document();
    doc.add(newStringField("id", "0", Field.Store.YES));
    doc.add(newTextField("field", "wizard the the the the the oz", Field.Store.NO));
    doc.add(new FloatDocValuesField("final-score", 1.0f));
    w.addDocument(doc);
    doc = new Document();
    doc.add(newStringField("id", "1", Field.Store.YES));
    // 1 extra token, but wizard and oz are close;
    doc.add(newTextField("field", "wizard oz the the the the the the", Field.Store.NO));
    doc.add(new FloatDocValuesField("final-score", 2.0f));
    w.addDocument(doc);
    final IndexReader r = w.getReader();
    w.close();
    // Do ordinary BooleanQuery:
    final BooleanQuery.Builder bqBuilder = new BooleanQuery.Builder();
    bqBuilder.add(new TermQuery(new Term("field", "wizard")), BooleanClause.Occur.SHOULD);
    bqBuilder.add(new TermQuery(new Term("field", "oz")), BooleanClause.Occur.SHOULD);
    final IndexSearcher searcher = getSearcher(r);
    // first run the standard query
    TopDocs hits = searcher.search(bqBuilder.build(), 10);
    assertEquals(2, hits.totalHits);
    assertEquals("0", searcher.doc(hits.scoreDocs[0].doc).get("id"));
    assertEquals("1", searcher.doc(hits.scoreDocs[1].doc).get("id"));
    final List<Feature> features = makeFieldValueFeatures(new int[] { 0, 1, 2 }, "final-score");
    final List<Normalizer> norms = new ArrayList<Normalizer>(Collections.nCopies(features.size(), IdentityNormalizer.INSTANCE));
    final List<Feature> allFeatures = makeFieldValueFeatures(new int[] { 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 }, "final-score");
    final LTRScoringModel ltrScoringModel = TestLinearModel.createLinearModel("test", features, norms, "test", allFeatures, null);
    final LTRRescorer rescorer = new LTRRescorer(new LTRScoringQuery(ltrScoringModel));
    hits = rescorer.rescore(searcher, hits, 2);
    // rerank using the field final-score
    assertEquals("1", searcher.doc(hits.scoreDocs[0].doc).get("id"));
    assertEquals("0", searcher.doc(hits.scoreDocs[1].doc).get("id"));
    r.close();
    dir.close();
}

Example 20 with Feature

use of org.apache.solr.ltr.feature.Feature in project lucene-solr by apache.

the class ManagedFeatureStore method featuresAsManagedResources.

private static List<Object> featuresAsManagedResources(FeatureStore store) {
    final List<Feature> storedFeatures = store.getFeatures();
    final List<Object> features = new ArrayList<Object>(storedFeatures.size());
    for (final Feature f : storedFeatures) {
        final LinkedHashMap<String, Object> m = toFeatureMap(f);
        m.put(FEATURE_STORE_NAME_KEY, store.getName());
        features.add(m);
    }
    return features;
}