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

Examples of org.apache.mahout.cf.taste.impl.common.LongPrimitiveIterator.nextLong()

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    private int countPreferences(DataModel dataModel) throws TasteException {
      int numPreferences = 0;
      LongPrimitiveIterator userIDs = dataModel.getUserIDs();
      while (userIDs.hasNext()) {
        PreferenceArray preferencesFromUser = dataModel.getPreferencesFromUser(userIDs.nextLong());
        numPreferences += preferencesFromUser.length();
      }
      return numPreferences;
    }
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      preferences = new Preference[numPreferences];

      LongPrimitiveIterator userIDs = dataModel.getUserIDs();
      int index = 0;
      while (userIDs.hasNext()) {
        long userID = userIDs.nextLong();
        PreferenceArray preferencesFromUser = dataModel.getPreferencesFromUser(userID);
        for (Preference preference : preferencesFromUser) {
          preferences[index++] = preference;
        }
      }
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      itemIDs = new FastIDSet(dataModel.getNumItems());
      preferences = Lists.newArrayList();

      LongPrimitiveIterator userIDsIterator = dataModel.getUserIDs();
      while (userIDsIterator.hasNext()) {
        long userID = userIDsIterator.nextLong();
        userIDs.add(userID);
        for (Preference preference : dataModel.getPreferencesFromUser(userID)) {
          itemIDs.add(preference.getItemID());
          preferences.add(new GenericPreference(userID, preference.getItemID(), preference.getValue()));
        }
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                              String tag) throws TasteException {
    printHeader();
    LongPrimitiveIterator users = recommender1.getDataModel().getUserIDs();

    while (users.hasNext()) {
      long userID = users.nextLong();
      List<RecommendedItem> recs1 = recommender1.recommend(userID, samples);
      List<RecommendedItem> recs2 = recommender2.recommend(userID, samples);
      FastIDSet commonSet = new FastIDSet();
      long maxItemID = setBits(commonSet, recs1, samples);
      FastIDSet otherSet = new FastIDSet();
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                              RunningAverage tracker,
                              String tag) throws TasteException {
    printHeader();
    LongPrimitiveIterator users = recommender.getDataModel().getUserIDs();
    while (users.hasNext()) {
      long userID = users.nextLong();
      List<RecommendedItem> recs1 = recommender.recommend(userID, model.getNumItems());
      PreferenceArray prefs2 = model.getPreferencesFromUser(userID);
      prefs2.sortByValueReversed();
      FastIDSet commonSet = new FastIDSet();
      long maxItemID = setBits(commonSet, recs1, samples);
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                              RunningAverage tracker,
                              String tag) throws TasteException {
    printHeader();
    LongPrimitiveIterator users = model1.getUserIDs();
    while (users.hasNext()) {
      long userID = users.nextLong();
      PreferenceArray prefs1 = model1.getPreferencesFromUser(userID);
      PreferenceArray prefs2 = model2.getPreferencesFromUser(userID);
      prefs1.sortByValueReversed();
      prefs2.sortByValueReversed();
      FastIDSet commonSet = new FastIDSet();
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      long userID = entry.getKey();
      FastIDSet itemIDs = entry.getValue();
      itemIDSet.addAll(itemIDs);
      LongPrimitiveIterator it = itemIDs.iterator();
      while (it.hasNext()) {
        long itemID = it.nextLong();
        FastIDSet userIDs = preferenceForItems.get(itemID);
        if (userIDs == null) {
          userIDs = new FastIDSet(2);
          preferenceForItems.put(itemID, userIDs);
        }
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   */
  public static FastByIDMap<FastIDSet> toDataMap(DataModel dataModel) throws TasteException {
    FastByIDMap<FastIDSet> data = new FastByIDMap<FastIDSet>(dataModel.getNumUsers());
    LongPrimitiveIterator it = dataModel.getUserIDs();
    while (it.hasNext()) {
      long userID = it.nextLong();
      data.put(userID, dataModel.getItemIDsFromUser(userID));
    }
    return data;
  }

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    PreferenceArray prefArray = new BooleanUserPreferenceArray(itemIDs.size());
    int i = 0;
    LongPrimitiveIterator it = itemIDs.iterator();
    while (it.hasNext()) {
      prefArray.setUserID(i, userID);
      prefArray.setItemID(i, it.nextLong());
      i++;
    }
    return prefArray;
  }
 
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    int numUsersWithRecommendations = 0;

    LongPrimitiveIterator it = dataModel.getUserIDs();
    while (it.hasNext()) {

      long userID = it.nextLong();

      if (random.nextDouble() >= evaluationPercentage) {
        // Skipped
        continue;
      }
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