Package org.apache.mahout.cf.taste.impl.common

Examples of org.apache.mahout.cf.taste.impl.common.FastIDSet.addAll()

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        FastIDSet cluster2 = nearestPair.getSecond();
        while (clusterSimilarity.getSimilarity(cluster1, cluster2) >= clusteringThreshold) {
          newClusters.remove(cluster1);
          newClusters.remove(cluster2);
          FastIDSet merged = new FastIDSet(cluster1.size() + cluster2.size());
          merged.addAll(cluster1);
          merged.addAll(cluster2);
          newClusters.add(merged);
          nearestPair = findNearestClusters(newClusters);
          if (nearestPair == null) {
            break;
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        while (clusterSimilarity.getSimilarity(cluster1, cluster2) >= clusteringThreshold) {
          newClusters.remove(cluster1);
          newClusters.remove(cluster2);
          FastIDSet merged = new FastIDSet(cluster1.size() + cluster2.size());
          merged.addAll(cluster1);
          merged.addAll(cluster2);
          newClusters.add(merged);
          nearestPair = findNearestClusters(newClusters);
          if (nearestPair == null) {
            break;
          }
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        FastIDSet cluster1 = nearestPair.getFirst();
        FastIDSet cluster2 = nearestPair.getSecond();
        newClusters.remove(cluster1);
        newClusters.remove(cluster2);
        FastIDSet merged = new FastIDSet(cluster1.size() + cluster2.size());
        merged.addAll(cluster1);
        merged.addAll(cluster2);
        newClusters.add(merged);
      }
    }
  }
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        FastIDSet cluster2 = nearestPair.getSecond();
        newClusters.remove(cluster1);
        newClusters.remove(cluster2);
        FastIDSet merged = new FastIDSet(cluster1.size() + cluster2.size());
        merged.addAll(cluster1);
        merged.addAll(cluster2);
        newClusters.add(merged);
      }
    }
  }
 
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  private List<RecommendedItem> computeTopRecsForCluster(FastIDSet cluster) throws TasteException {
    DataModel dataModel = getDataModel();
    FastIDSet possibleItemIDs = new FastIDSet();
    LongPrimitiveIterator it = cluster.iterator();
    while (it.hasNext()) {
      possibleItemIDs.addAll(dataModel.getItemIDsFromUser(it.nextLong()));
    }
   
    TopItems.Estimator<Long> estimator = new Estimator(cluster);
   
    List<RecommendedItem> topItems =
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public final class AllUnknownItemsCandidateItemsStrategyTest extends TasteTestCase {

  @Test 
  public void testStrategy() throws TasteException {
    FastIDSet allItemIDs = new FastIDSet();
    allItemIDs.addAll(new long[] { 1L, 2L, 3L });

    FastIDSet preferredItemIDs = new FastIDSet(1);
    preferredItemIDs.add(2L);
   
    DataModel dataModel = EasyMock.createMock(DataModel.class);
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        }
      }

      // Make new merged cluster
      FastIDSet merged = new FastIDSet(cluster1.size() + cluster2.size());
      merged.addAll(cluster1);
      merged.addAll(cluster2);

      // Compare against other clusters; update queue if needed
      // That new pair we're just adding might be pretty close to something else, so
      // catch that case here and put it back into our queue
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      }

      // Make new merged cluster
      FastIDSet merged = new FastIDSet(cluster1.size() + cluster2.size());
      merged.addAll(cluster1);
      merged.addAll(cluster2);

      // Compare against other clusters; update queue if needed
      // That new pair we're just adding might be pretty close to something else, so
      // catch that case here and put it back into our queue
      for (FastIDSet cluster : clusters) {
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    DataModel dataModel = getDataModel();
    FastIDSet possibleItemIDs = new FastIDSet();
    LongPrimitiveIterator it = cluster.iterator();
    while (it.hasNext()) {
      possibleItemIDs.addAll(dataModel.getItemIDsFromUser(it.next()));
    }

    TopItems.Estimator<Long> estimator = new Estimator(cluster);

    List<RecommendedItem> topItems =
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    for (long itemID : itemIDs) {
      PreferenceArray prefs = model.getPreferencesForItem(itemID);
      int size = prefs.length();
      for (int i = 0; i < size; i++) {
        long userID = prefs.get(i).getUserID();
        possibleItemsIDs.addAll(model.getItemIDsFromUser(userID));
      }
    }
    possibleItemsIDs.removeAll(itemIDs);
    return TopItems.getTopItems(howMany, possibleItemsIDs.iterator(), null, estimator);
  }
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