List of estimatePreference() Examples

Examples of estimatePreference()

org.apache.hama.ml.recommendation.cf.OnlineCF.estimatePreference()
org.apache.mahout.cf.taste.recommender.Recommender.estimatePreference()
@param userID user ID whose preference is to be estimated @param itemID item ID to estimate preference for @return an estimated preference if the user has not expressed a preference for the item, or else theuser's actual preference for the item. If a preference cannot be estimated, returns {@link Double#NaN} @throws TasteException if an error occurs while accessing the {@link DataModel}

Examples of org.apache.mahout.cf.taste.recommender.Recommender.estimatePreference()

  }


  @Test
  public void testEstimatePref() throws Exception {
    Recommender recommender = buildRecommender();
    assertEquals(0.1f, recommender.estimatePreference(1, 2), EPSILON);
  }


  @Test
  public void testBestRating() throws Exception {
    Recommender recommender = buildRecommender();

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Examples of org.apache.mahout.cf.taste.recommender.Recommender.estimatePreference()

    assertEquals(8, recommendCount.intValue());
    cachingRecommender.recommend(2, 1, null);
    assertEquals(9, recommendCount.intValue());


    cachingRecommender.refresh(null);
    cachingRecommender.estimatePreference(1, 1);
    assertEquals(10, recommendCount.intValue());
    cachingRecommender.estimatePreference(1, 2);
    assertEquals(11, recommendCount.intValue());
    cachingRecommender.estimatePreference(1, 2);
    assertEquals(11, recommendCount.intValue());

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Examples of org.apache.mahout.cf.taste.recommender.Recommender.estimatePreference()

    assertEquals(9, recommendCount.intValue());


    cachingRecommender.refresh(null);
    cachingRecommender.estimatePreference(1, 1);
    assertEquals(10, recommendCount.intValue());
    cachingRecommender.estimatePreference(1, 2);
    assertEquals(11, recommendCount.intValue());
    cachingRecommender.estimatePreference(1, 2);
    assertEquals(11, recommendCount.intValue());
  }

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Examples of org.apache.mahout.cf.taste.recommender.Recommender.estimatePreference()

  }


  @Test
  public void testEstimatePref() throws Exception {
    Recommender recommender = buildRecommender();
    assertEquals(0.1f, recommender.estimatePreference(1, 2), EPSILON);
  }


  @Test
  public void testBestRating() throws Exception {
    Recommender recommender = buildRecommender();

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Examples of org.apache.mahout.cf.taste.recommender.Recommender.estimatePreference()

    cachingRecommender.refresh(null);
    cachingRecommender.estimatePreference(1, 1);
    assertEquals(10, recommendCount.intValue());
    cachingRecommender.estimatePreference(1, 2);
    assertEquals(11, recommendCount.intValue());
    cachingRecommender.estimatePreference(1, 2);
    assertEquals(11, recommendCount.intValue());
  }


}

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Examples of org.apache.mahout.cf.taste.recommender.Recommender.estimatePreference()

  }


  @Test
  public void testEstimatePref() throws Exception {
    Recommender recommender = buildRecommender();
    assertEquals(0.1f, recommender.estimatePreference(1, 2), EPSILON);
  }


  /**
   * Contributed test case that verifies fix for bug
   * <a href="http://sourceforge.net/tracker/index.php?func=detail&amp;aid=1396128&amp;group_id=138771&amp;atid=741665">

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Examples of org.apache.mahout.cf.taste.recommender.Recommender.estimatePreference()

  }


  @Test
  public void testEstimatePref() throws Exception {
    Recommender recommender = buildRecommender();
    assertEquals(0.34803885284992736, recommender.estimatePreference(1, 2), EPSILON);
  }


  @Test
  public void testBestRating() throws Exception {
    DataModel dataModel = getDataModel(

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Examples of org.apache.mahout.cf.taste.recommender.Recommender.estimatePreference()

                    {0.2, 0.3, 0.6},
                    {0.3, 0.3, 0.3},
            });


    Recommender recommender = new SlopeOneRecommender(dataModel);
    assertEquals(0.3257085f, recommender.estimatePreference(1, 2), EPSILON);
  }


  private static Recommender buildRecommender() throws TasteException {
    DataModel dataModel = getDataModel();
    return new SlopeOneRecommender(dataModel);

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Examples of org.apache.mahout.cf.taste.recommender.Recommender.estimatePreference()

    users.add(getUser("test4", 0.7, 0.3, 0.8, 0.9));
    DataModel dataModel = new GenericDataModel(users);
    UserSimilarity similarity = new PearsonCorrelationSimilarity(dataModel);
    ClusterSimilarity clusterSimilarity = new FarthestNeighborClusterSimilarity(similarity);
    Recommender recommender = new TreeClusteringRecommender(dataModel, clusterSimilarity, 2);
    assertEquals(0.9, recommender.estimatePreference("test3", "3"));
  }


  public void testBestRating() throws Exception {
    List<User> users = new ArrayList<User>(4);
    users.add(getUser("test1", 0.1, 0.3));

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Examples of org.apache.mahout.cf.taste.recommender.Recommender.estimatePreference()

    assertEquals(originalRecommended.get(1).getItem(), rescoredRecommended.get(0).getItem());
  }


  public void testEstimatePref() throws Exception {
    Recommender recommender = buildRecommender();
    assertEquals(0.34803885284992736, recommender.estimatePreference("test1", "2"), EPSILON);
  }


  public void testBestRating() throws Exception {
    List<User> users = new ArrayList<User>(3);
    users.add(getUser("test1", 0.0, 0.3));

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