Examples of opennlp.tools.util.eval.Mean

opennlp.tools.util.eval.Mean
Calculates the arithmetic mean of values added with the {@link #add(double)} method.

    }


    // Clears the adaptive data which was created for the current document
    mNameFinder.clearAdaptiveData();


    documentConfidence = new Mean();
  }

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 */
public class MeanTest {


  @Test
  public void testMeanCalculation() {
    Mean a = new Mean();
    a.add(1);
    assertEquals(1, a.count());
    assertEquals(1d, a.mean(), 0.00001d);
    
    a.add(1);
    assertEquals(2, a.count());
    assertEquals(1d, a.mean(), 0.00001d);
    a.toString();
    
    Mean b = new Mean();
    b.add(0.5);
    assertEquals(1, b.count());
    assertEquals(0.5d, b.mean(), 0.00001d);
    
    b.add(2);
    assertEquals(2, b.count());
    assertEquals(1.25d, b.mean(), 0.00001d);
    b.toString();
    
    Mean c = new Mean();
    assertEquals(0, c.count());
    assertEquals(0d, c.mean(), 0.00001d);
    c.toString();
  }

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    }


    // Clears the adaptive data which was created for the current document
    mNameFinder.clearAdaptiveData();


    documentConfidence = new Mean();
  }

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     *          the predicted pos tag
     */
    private void add(String tok, String ref, String pred) {
      // token stats
      if (!tokAccuracies.containsKey(tok)) {
        tokAccuracies.put(tok, new Mean());
        tokOcurrencies.put(tok, new Counter());
        tokErrors.put(tok, new Counter());
      }
      tokOcurrencies.get(tok).increment();

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     *          the predicted pos tag
     */
    private void add(String tok, String ref, String pred) {
      // token stats
      if (!tokAccuracies.containsKey(tok)) {
        tokAccuracies.put(tok, new Mean());
        tokOcurrencies.put(tok, new Counter());
        tokErrors.put(tok, new Counter());
      }
      tokOcurrencies.get(tok).increment();

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     *          the predicted pos tag
     */
    private void add(String tok, String ref, String pred) {
      // token stats
      if (!tokAccuracies.containsKey(tok)) {
        tokAccuracies.put(tok, new Mean());
        tokOcurrencies.put(tok, new Counter());
        tokErrors.put(tok, new Counter());
      }
      tokOcurrencies.get(tok).increment();

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    }


    // Clears the adaptive data which was created for the current document
    mNameFinder.clearAdaptiveData();


    documentConfidence = new Mean();
  }

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Related Classes of opennlp.tools.util.eval.Mean

opennlp.tools.cmdline.doccat.DoccatFineGrainedReportListener$Stats

opennlp.tools.cmdline.postag.POSTaggerFineGrainedReportListener$Stats

opennlp.tools.util.eval.MeanTest

opennlp.uima.namefind.NameFinder

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