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OnlineCF recommender = new OnlineCF(); 
recommender.setInputPreferences(convertedOutputPath); 
recommender.setIteration(150); 
recommender.setMatrixRank(3); 
recommender.setSkipCount(1); // after how many steps we should synchronize values in each task 
recommender.setUpdateFunction(MeanAbsError.class); 
recommender.setOutputPath(outputFileName); 
recommender.train();

// estimate score 
double estimatedScore = recommender.estimatePreference(userId, itemId);

// estimate user similarities 
double userSimilarity = recommender.calculateUserSimilarity(user1, user2); 
// Pair<K, V> - where K predicted similar user, V predicted similarity score 
List<Pair<Long, Double>> similarUsers = recommender.getMostSimilarUsers(userId, count);

// estimate item similarities 
double itemSimilarity = recommender.calculateItemSimilarity(item1, item2); 
// Pair<K, V> - where K predicted similar item, V predicted similarity score 
List<Pair<Long, Double>> similarItems = recommender.getMostSimilarItems(itemId, count);