Esempio n. 1
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  @Test
  public void testIris() throws ScoreException {
    double scoreBetter = subject.score(FakeClustering.iris());
    double scoreWorser = subject.score(FakeClustering.irisWrong4());

    // should recognize better clustering
    assertEquals(true, subject.isBetter(scoreBetter, scoreWorser));
  }
Esempio n. 2
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  /** Test of score method, of class NMI. */
  @Test
  public void testScore_Clustering_Dataset() throws ScoreException {
    measure(FakeClustering.iris(), 1.0);

    double score = measure(irisWrong, 0.6545182434318744);
    double score2 = measure(FakeClustering.irisWrong(), irisCorrect, 0.06793702240876041);

    assertTrue(score2 < score);
  }
Esempio n. 3
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  /** Test of score method, of class NMI. */
  @Test
  public void testScore_Clustering_Clustering() throws ScoreException {
    // this is fixed clustering which correspods to true classes in dataset
    measure(FakeClustering.iris(), FakeClustering.iris(), 1.0);

    double score = measure(irisWrong, irisCorrect, 0.6496820278112178);

    double score2 = measure(FakeClustering.irisWrong(), irisCorrect, 0.06793702240876041);
    assertTrue(score2 < score);
  }
Esempio n. 4
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  /** Test of score method, of class F-measure. */
  @Test
  public void testScore_Clustering_Dataset() throws ScoreException {
    double score;
    // each cluster should have this scores:
    // Cabernet = 0.7200
    // Syrah = 0.5555
    // Pinot = 0.7272
    score =
        measure(FakeClustering.wineClustering(), FakeClustering.wineCorrect(), 0.48132780082987553);

    // when using class labels result should be the same
    measure(FakeClustering.wineClustering(), score);
  }
Esempio n. 5
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 public ExternalTest() {
   ext100p2 = FakeClustering.ext100p2();
   ext100p3 = FakeClustering.ext100p3();
 }
Esempio n. 6
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 public NMIsqrtTest() throws FileNotFoundException, IOException {
   irisCorrect = FakeClustering.iris();
   irisWrong = FakeClustering.irisWrong2();
   subject = new NMIsqrt();
 }
Esempio n. 7
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 @Test
 public void testMostlyWrong() throws ScoreException {
   double score = subject.score(FakeClustering.irisMostlyWrong());
   System.out.println("f-measure (mw) = " + score);
   assertEquals(true, score < 0.5);
 }
Esempio n. 8
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 /**
  * Check against definition (and tests in R package clusterCrit)
  * https://cran.r-project.org/web/packages/clusterCrit/index.html
  *
  * <p>NOTE: There's a small problem with precision of floating point operations. First 7 decimal
  * digits seems to match.
  */
 @Test
 public void testClusterCrit() throws ScoreException {
   double score = subject.score(FakeClustering.int100p4());
   // clustCrit: 105.942129943902
   assertEquals(105.942129943902, score, delta);
 }