Example usage for org.apache.mahout.cf.taste.impl.common RunningAverage getCount

Introduction

In this page you can find the example usage for org.apache.mahout.cf.taste.impl.common RunningAverage getCount.

Prototype

int getCount();

Source Link

Usage

From source file:net.ufida.info.mahout.common.MemoryDiffStorage.java

License:Apache License

@Override
public void removeItemPref(long userID, long itemIDA, float prefValue) throws TasteException {
    PreferenceArray userPreferences = dataModel.getPreferencesFromUser(userID);
    try {//from   www  . j  ava  2 s .c  om
        buildAverageDiffsLock.writeLock().lock();

        FastByIDMap<RunningAverage> aMap = averageDiffs.get(itemIDA);

        int length = userPreferences.length();
        for (int i = 0; i < length; i++) {

            long itemIDB = userPreferences.getItemID(i);
            float bValue = userPreferences.getValue(i);

            if (itemIDA < itemIDB) {

                if (aMap != null) {
                    RunningAverage average = aMap.get(itemIDB);
                    if (average != null) {
                        if (average.getCount() <= 1) {
                            aMap.remove(itemIDB);
                        } else {
                            average.removeDatum(bValue - prefValue);
                        }
                    }
                }

            } else if (itemIDA > itemIDB) {

                FastByIDMap<RunningAverage> bMap = averageDiffs.get(itemIDB);
                if (bMap != null) {
                    RunningAverage average = bMap.get(itemIDA);
                    if (average != null) {
                        if (average.getCount() <= 1) {
                            aMap.remove(itemIDA);
                        } else {
                            average.removeDatum(prefValue - bValue);
                        }
                    }
                }

            }
        }

    } finally {
        buildAverageDiffsLock.writeLock().unlock();
    }
}

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From source file:net.ufida.info.mahout.common.MemoryDiffStorage.java

License:Apache License

private void pruneInconsequentialDiffs() {
    // Go back and prune inconsequential diffs. "Inconsequential" means, here, only represented by one
    // data point, so possibly unreliable
    Iterator<Map.Entry<Long, FastByIDMap<RunningAverage>>> it1 = averageDiffs.entrySet().iterator();
    while (it1.hasNext()) {
        FastByIDMap<RunningAverage> map = it1.next().getValue();
        Iterator<Map.Entry<Long, RunningAverage>> it2 = map.entrySet().iterator();
        while (it2.hasNext()) {
            RunningAverage average = it2.next().getValue();
            if (average.getCount() <= 1) {
                it2.remove();/*from w w w  .j  a v  a 2 s  . c  o  m*/
            }
        }
        if (map.isEmpty()) {
            it1.remove();
        } else {
            map.rehash();
        }
    }
    averageDiffs.rehash();
}

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From source file:net.ufida.info.mahout.common.SlopeOneRecommender.java

License:Apache License

private float doEstimatePreference(long userID, long itemID) throws TasteException {
    double count = 0.0;
    double totalPreference = 0.0;
    PreferenceArray prefs = getDataModel().getPreferencesFromUser(userID);
    RunningAverage[] averages = diffStorage.getDiffs(userID, itemID, prefs);
    int size = prefs.length();
    for (int i = 0; i < size; i++) {
        RunningAverage averageDiff = averages[i];
        if (averageDiff != null) {
            double averageDiffValue = averageDiff.getAverage();
            if (weighted) {
                double weight = averageDiff.getCount();
                if (stdDevWeighted) {
                    double stdev = ((RunningAverageAndStdDev) averageDiff).getStandardDeviation();
                    if (!Double.isNaN(stdev)) {
                        weight /= 1.0 + stdev;
                    }//from w w  w  . ja  v  a  2  s. co m
                    // If stdev is NaN, then it is because count is 1. Because we're weighting by count,
                    // the weight is already relatively low. We effectively assume stdev is 0.0 here and
                    // that is reasonable enough. Otherwise, dividing by NaN would yield a weight of NaN
                    // and disqualify this pref entirely
                    // (Thanks Daemmon)
                }
                totalPreference += weight * (prefs.getValue(i) + averageDiffValue);
                count += weight;
            } else {
                totalPreference += prefs.getValue(i) + averageDiffValue;
                count += 1.0;
            }
        }
    }
    if (count <= 0.0) {
        RunningAverage itemAverage = diffStorage.getAverageItemPref(itemID);
        return itemAverage == null ? Float.NaN : (float) itemAverage.getAverage();
    } else {
        return (float) (totalPreference / count);
    }
}

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