lucene/classification/src/test/org/apache/lucene/classification/utils/TestConfusionMatrixGenerator.java

/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
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package org.apache.lucene.classification.utils;

import java.io.IOException;
import java.util.List;
import org.apache.lucene.analysis.MockAnalyzer;
import org.apache.lucene.classification.BM25NBClassifier;
import org.apache.lucene.classification.BooleanPerceptronClassifier;
import org.apache.lucene.classification.CachingNaiveBayesClassifier;
import org.apache.lucene.classification.ClassificationResult;
import org.apache.lucene.classification.ClassificationTestBase;
import org.apache.lucene.classification.Classifier;
import org.apache.lucene.classification.KNearestFuzzyClassifier;
import org.apache.lucene.classification.KNearestNeighborClassifier;
import org.apache.lucene.classification.SimpleNaiveBayesClassifier;
import org.apache.lucene.index.LeafReader;
import org.apache.lucene.util.BytesRef;
import org.junit.Test;

/** Tests for {@link ConfusionMatrixGenerator} */
public class TestConfusionMatrixGenerator extends ClassificationTestBase<Object> {

  @Test
  public void testGetConfusionMatrix() throws Exception {
    LeafReader reader = null;
    try {
      MockAnalyzer analyzer = new MockAnalyzer(random());
      reader = getSampleIndex(analyzer);
      Classifier<BytesRef> classifier =
          new Classifier<BytesRef>() {
            @Override
            public ClassificationResult<BytesRef> assignClass(String text) throws IOException {
              return new ClassificationResult<>(
                  new BytesRef(), 1 / (1 + Math.exp(-random().nextInt())));
            }

            @Override
            public List<ClassificationResult<BytesRef>> getClasses(String text) throws IOException {
              return null;
            }

            @Override
            public List<ClassificationResult<BytesRef>> getClasses(String text, int max)
                throws IOException {
              return null;
            }
          };
      ConfusionMatrixGenerator.ConfusionMatrix confusionMatrix =
          ConfusionMatrixGenerator.getConfusionMatrix(
              reader, classifier, categoryFieldName, textFieldName, -1);
      assertNotNull(confusionMatrix);
      assertNotNull(confusionMatrix.getLinearizedMatrix());
      assertEquals(7, confusionMatrix.getNumberOfEvaluatedDocs());
      double avgClassificationTime = confusionMatrix.getAvgClassificationTime();
      assertTrue(avgClassificationTime >= 0d);
      double accuracy = confusionMatrix.getAccuracy();
      assertTrue(accuracy >= 0d);
      assertTrue(accuracy <= 1d);
      double precision = confusionMatrix.getPrecision();
      assertTrue(precision >= 0d);
      assertTrue(precision <= 1d);
      double recall = confusionMatrix.getRecall();
      assertTrue(recall >= 0d);
      assertTrue(recall <= 1d);
      double f1Measure = confusionMatrix.getF1Measure();
      assertTrue(f1Measure >= 0d);
      assertTrue(f1Measure <= 1d);
    } finally {
      if (reader != null) {
        reader.close();
      }
    }
  }

  @Test
  public void testGetConfusionMatrixWithSNB() throws Exception {
    LeafReader reader = null;
    try {
      MockAnalyzer analyzer = new MockAnalyzer(random());
      reader = getSampleIndex(analyzer);
      Classifier<BytesRef> classifier =
          new SimpleNaiveBayesClassifier(reader, analyzer, null, categoryFieldName, textFieldName);
      ConfusionMatrixGenerator.ConfusionMatrix confusionMatrix =
          ConfusionMatrixGenerator.getConfusionMatrix(
              reader, classifier, categoryFieldName, textFieldName, -1);
      checkCM(confusionMatrix);
    } finally {
      if (reader != null) {
        reader.close();
      }
    }
  }

  private void checkCM(ConfusionMatrixGenerator.ConfusionMatrix confusionMatrix) {
    assertNotNull(confusionMatrix);
    assertNotNull(confusionMatrix.getLinearizedMatrix());
    assertEquals(7, confusionMatrix.getNumberOfEvaluatedDocs());
    assertTrue(confusionMatrix.getAvgClassificationTime() >= 0d);
    double accuracy = confusionMatrix.getAccuracy();
    assertTrue(accuracy >= 0d);
    assertTrue(accuracy <= 1d);
    double precision = confusionMatrix.getPrecision();
    assertTrue(precision >= 0d);
    assertTrue(precision <= 1d);
    double recall = confusionMatrix.getRecall();
    assertTrue(recall >= 0d);
    assertTrue(recall <= 1d);
    double f1Measure = confusionMatrix.getF1Measure();
    assertTrue(f1Measure >= 0d);
    assertTrue(f1Measure <= 1d);
  }

  @Test
  public void testGetConfusionMatrixWithBM25NB() throws Exception {
    LeafReader reader = null;
    try {
      MockAnalyzer analyzer = new MockAnalyzer(random());
      reader = getSampleIndex(analyzer);
      Classifier<BytesRef> classifier =
          new BM25NBClassifier(reader, analyzer, null, categoryFieldName, textFieldName);
      ConfusionMatrixGenerator.ConfusionMatrix confusionMatrix =
          ConfusionMatrixGenerator.getConfusionMatrix(
              reader, classifier, categoryFieldName, textFieldName, -1);
      checkCM(confusionMatrix);
    } finally {
      if (reader != null) {
        reader.close();
      }
    }
  }

  @Test
  public void testGetConfusionMatrixWithCNB() throws Exception {
    LeafReader reader = null;
    try {
      MockAnalyzer analyzer = new MockAnalyzer(random());
      reader = getSampleIndex(analyzer);
      Classifier<BytesRef> classifier =
          new CachingNaiveBayesClassifier(reader, analyzer, null, categoryFieldName, textFieldName);
      ConfusionMatrixGenerator.ConfusionMatrix confusionMatrix =
          ConfusionMatrixGenerator.getConfusionMatrix(
              reader, classifier, categoryFieldName, textFieldName, -1);
      checkCM(confusionMatrix);
    } finally {
      if (reader != null) {
        reader.close();
      }
    }
  }

  @Test
  public void testGetConfusionMatrixWithKNN() throws Exception {
    LeafReader reader = null;
    try {
      MockAnalyzer analyzer = new MockAnalyzer(random());
      reader = getSampleIndex(analyzer);
      Classifier<BytesRef> classifier =
          new KNearestNeighborClassifier(
              reader, null, analyzer, null, 1, 0, 0, categoryFieldName, textFieldName);
      ConfusionMatrixGenerator.ConfusionMatrix confusionMatrix =
          ConfusionMatrixGenerator.getConfusionMatrix(
              reader, classifier, categoryFieldName, textFieldName, -1);
      checkCM(confusionMatrix);
    } finally {
      if (reader != null) {
        reader.close();
      }
    }
  }

  @Test
  public void testGetConfusionMatrixWithFLTKNN() throws Exception {
    LeafReader reader = null;
    try {
      MockAnalyzer analyzer = new MockAnalyzer(random());
      reader = getSampleIndex(analyzer);
      Classifier<BytesRef> classifier =
          new KNearestFuzzyClassifier(
              reader, null, analyzer, null, 1, categoryFieldName, textFieldName);
      ConfusionMatrixGenerator.ConfusionMatrix confusionMatrix =
          ConfusionMatrixGenerator.getConfusionMatrix(
              reader, classifier, categoryFieldName, textFieldName, -1);
      checkCM(confusionMatrix);
    } finally {
      if (reader != null) {
        reader.close();
      }
    }
  }

  @Test
  public void testGetConfusionMatrixWithBP() throws Exception {
    LeafReader reader = null;
    try {
      MockAnalyzer analyzer = new MockAnalyzer(random());
      reader = getSampleIndex(analyzer);
      Classifier<Boolean> classifier =
          new BooleanPerceptronClassifier(
              reader, analyzer, null, 1, null, booleanFieldName, textFieldName);
      ConfusionMatrixGenerator.ConfusionMatrix confusionMatrix =
          ConfusionMatrixGenerator.getConfusionMatrix(
              reader, classifier, booleanFieldName, textFieldName, -1);
      checkCM(confusionMatrix);
      assertTrue(confusionMatrix.getPrecision("true") >= 0d);
      assertTrue(confusionMatrix.getPrecision("true") <= 1d);
      assertTrue(confusionMatrix.getPrecision("false") >= 0d);
      assertTrue(confusionMatrix.getPrecision("false") <= 1d);
      assertTrue(confusionMatrix.getRecall("true") >= 0d);
      assertTrue(confusionMatrix.getRecall("true") <= 1d);
      assertTrue(confusionMatrix.getRecall("false") >= 0d);
      assertTrue(confusionMatrix.getRecall("false") <= 1d);
      assertTrue(confusionMatrix.getF1Measure("true") >= 0d);
      assertTrue(confusionMatrix.getF1Measure("true") <= 1d);
      assertTrue(confusionMatrix.getF1Measure("false") >= 0d);
      assertTrue(confusionMatrix.getF1Measure("false") <= 1d);
    } finally {
      if (reader != null) {
        reader.close();
      }
    }
  }
}