public IEnumerable <RatingPredictionRecommendation> GetRecommendations(MalUserListEntries inputForUser, int numRecommendationsToTryToGet)
{
IBasicInputForUser basicInput = inputForUser.AsBasicInput(m_minEpisodesToCountIncomplete, m_useDropped,
additionalOkToRecommendPredicate: (animeId) => m_userCountByAnime.ContainsKey(animeId) && m_userCountByAnime[animeId] >= m_minUsersToCountAnime
);
return(m_recommender.GetRecommendations(basicInput, numRecommendationsToTryToGet));
}
public IEnumerable <RatingPredictionRecommendation> GetRecommendations(IBasicInputForUser userRatings, int numRecommendationsToTryToGet)
{
IList <Tuple <int, float> > userMediaLiteRatings = new List <Tuple <int, float> >();
foreach (KeyValuePair <int, float> realRating in userRatings.Ratings)
{
int realItemId = realRating.Key;
float score = realRating.Value;
// Do not pass in items that MyMediaLite does not know about, it will crash
if (m_realItemIdToMediaLiteItemId.ContainsKey(realItemId))
{
int mediaLiteItemId = m_realItemIdToMediaLiteItemId[realItemId];
userMediaLiteRatings.Add(new Tuple <int, float>(mediaLiteItemId, score));
}
}
IList <Tuple <int, float> > mediaLitePredictions = m_recommender.ScoreItems(userMediaLiteRatings);
List <RatingPredictionRecommendation> recs = new List <RatingPredictionRecommendation>();
foreach (Tuple <int, float> prediction in mediaLitePredictions.OrderByDescending(p => p.Item2))
{
int mediaLiteItemId = prediction.Item1;
float predictedScore = prediction.Item2;
int realItemId = m_mediaLiteItemIdToRealItemId[mediaLiteItemId];
if (userRatings.ItemIsOkToRecommend(realItemId))
{
recs.Add(new RatingPredictionRecommendation(realItemId, predictedScore));
if (recs.Count >= numRecommendationsToTryToGet)
{
break;
}
}
}
return(recs);
}
public void Train(IBasicTrainingData <IBasicInputForUser> trainingData)
{
m_realUserIdToMediaLiteUserId = new Dictionary <int, int>();
m_mediaLiteUserIdToRealUserId = new Dictionary <int, int>();
m_nextMediaLiteUserId = 0;
m_realItemIdToMediaLiteItemId = new Dictionary <int, int>();
m_mediaLiteItemIdToRealItemId = new Dictionary <int, int>();
m_nextMediaLiteItemId = 0;
MyMediaLite.Data.Ratings mediaLiteRatings = new MyMediaLite.Data.Ratings();
foreach (KeyValuePair <int, IBasicInputForUser> userRatingsPair in trainingData.Users)
{
int userId = userRatingsPair.Key;
IBasicInputForUser ratings = userRatingsPair.Value;
m_realUserIdToMediaLiteUserId[userId] = m_nextMediaLiteUserId;
m_mediaLiteUserIdToRealUserId[m_nextMediaLiteUserId] = userId;
m_nextMediaLiteUserId++;
foreach (KeyValuePair <int, float> rating in ratings.Ratings)
{
int itemId = rating.Key;
float score = rating.Value;
if (!m_realItemIdToMediaLiteItemId.ContainsKey(itemId))
{
m_realItemIdToMediaLiteItemId[itemId] = m_nextMediaLiteItemId;
m_mediaLiteItemIdToRealItemId[m_nextMediaLiteItemId] = itemId;
m_nextMediaLiteItemId++;
}
mediaLiteRatings.Add(m_realUserIdToMediaLiteUserId[userId], m_realItemIdToMediaLiteItemId[itemId], score);
}
}
m_recommender.Ratings = mediaLiteRatings;
m_recommender.Train();
}
