Package org.apache.mahout.classifier.bayes.model

Examples of org.apache.mahout.classifier.bayes.model.ClassifierContext

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  }

  @Test
  public void test() throws Exception {
    ClassifierContext classifier = new ClassifierContext(algorithm, store);
    String[] document = {"aa", "ff"};
    ClassifierResult result = classifier.classifyDocument(document, "unknown");
    assertNotNull("category is null and it shouldn't be", result);
    assertEquals(result + " is not equal to e", "e", result.getLabel());
   
    document = new String[] {"dd"};
    result = classifier.classifyDocument(document, "unknown");
    assertNotNull("category is null and it shouldn't be", result);
    assertEquals(result + " is not equal to d", "d", result.getLabel());
   
    document = new String[] {"cc"};
    result = classifier.classifyDocument(document, "unknown");
    assertNotNull("category is null and it shouldn't be", result);
    assertEquals(result + " is not equal to d", "d", result.getLabel());
  }
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    assertEquals(result + " is not equal to d", "d", result.getLabel());
  }

  @Test
  public void testResults() throws Exception {
    ClassifierContext classifier = new ClassifierContext(algorithm, store);
    String[] document = {"aa", "ff"};
    ClassifierResult result = classifier.classifyDocument(document, "unknown");
    assertNotNull("category is null and it shouldn't be", result);
  }
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      }
     
    } else {
      throw new IllegalArgumentException("Unrecognized dataSource type: " + params.get("dataSource"));
    }
    ClassifierContext classifier = new ClassifierContext(algorithm, datastore);
    classifier.initialize();
    ResultAnalyzer resultAnalyzer = new ResultAnalyzer(classifier.getLabels(), params.get("defaultCat"));
    TimingStatistics totalStatistics = new TimingStatistics();
    if (subdirs != null) {
     
      for (File file : subdirs) {
        if (verbose) {
          log.info("--------------");
          log.info("Testing: {}", file);
        }
        TimingStatistics operationStats = new TimingStatistics();
       
        long lineNum = 0;
        for (String line : new FileLineIterable(new File(file.getPath()), Charset.forName(params
            .get("encoding")), false)) {
         
          Map<String,List<String>> document = new NGrams(line, Integer.parseInt(params.get("gramSize")))
              .generateNGrams();
          for (Map.Entry<String,List<String>> stringListEntry : document.entrySet()) {
            String correctLabel = stringListEntry.getKey();
            List<String> strings = stringListEntry.getValue();
            TimingStatistics.Call call = operationStats.newCall();
            TimingStatistics.Call outercall = totalStatistics.newCall();
            ClassifierResult classifiedLabel = classifier.classifyDocument(strings.toArray(new String[strings
                .size()]), params.get("defaultCat"));
            call.end();
            outercall.end();
            boolean correct = resultAnalyzer.addInstance(correctLabel, classifiedLabel);
            if (verbose) {
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        }
       
      } else {
        throw new IllegalArgumentException("Unrecognized dataSource type: " + params.get("dataSource"));
      }
      classifier = new ClassifierContext(algorithm, datastore);
      classifier.initialize();
     
      defaultCategory = params.get("defaultCat");
      gramSize = params.getGramSize();
    } catch (IOException ex) {
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Related Classes of org.apache.mahout.classifier.bayes.model.ClassifierContext

  • org.apache.mahout.classifier.bayes.BayesClassifierSelfTest
  • org.apache.mahout.classifier.bayes.BayesClassifierTest
  • org.apache.mahout.classifier.bayes.CBayesClassifierTest
  • org.apache.mahout.classifier.bayes.mapreduce.bayes.BayesClassifierMapper
  • org.apache.mahout.classifier.bayes.TestClassifier
  • org.apache.mahout.classifier.Classify
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