public static void TestAllRecommenders()
{
UserBehaviorDatabaseParser dbp = new UserBehaviorDatabaseParser();
UserBehaviorDatabase db = dbp.LoadUserBehaviorDatabase("UserBehaviour.txt");
//var ubt = new UserBehaviorTransformer(db);
//var uart = ubt.GetUserArticleRatingsTable();
//uart.SaveSparcityVisual("sparcity.bmp");
//uart.SaveUserRatingDistribution("distrib.csv");
//uart.SaveArticleRatingDistribution("distriba.csv");
var rate = new LinearRater();
var sp = new DaySplitter(db, 5);
var uc = new CorrelationUserComparer();
//var rr = new RandomRecommender();
//rr.Train(sp.TrainingDB);
//ScoreResults scores5 = rr.Score(sp.TestingDB, rate);
//TestResults results5 = rr.Test(sp.TestingDB, 30);
var ubc = new UserCollaborativeFilterRecommender(uc, rate, 30);
var mfr = new MatrixFactorizationRecommender(30, rate);
var icf = new ItemCollaborativeFilterRecommender(uc, rate, 30);
var hbr = new HybridRecommender(ubc, mfr, icf);
hbr.Train(sp.TrainingDB);
ScoreResults scores1 = hbr.Score(sp.TestingDB, rate);
TestResults results1 = hbr.Test(sp.TestingDB, 30);
ubc = new UserCollaborativeFilterRecommender(uc, rate, 30);
mfr = new MatrixFactorizationRecommender(30, rate);
icf = new ItemCollaborativeFilterRecommender(uc, rate, 30);
ubc.Train(sp.TrainingDB);
ScoreResults scores2 = ubc.Score(sp.TestingDB, rate);
TestResults results2 = ubc.Test(sp.TestingDB, 30);
mfr.Train(sp.TrainingDB);
ScoreResults scores3 = mfr.Score(sp.TestingDB, rate);
TestResults results3 = mfr.Test(sp.TestingDB, 30);
icf.Train(sp.TrainingDB);
ScoreResults scores4 = icf.Score(sp.TestingDB, rate);
TestResults results4 = icf.Test(sp.TestingDB, 30);
using (StreamWriter w = new StreamWriter("results.csv"))
{
w.WriteLine("model,rmse,users,user-solved,precision,recall");
w.WriteLine("UCF," + scores2.RootMeanSquareDifference + "," + results2.TotalUsers + "," + results2.UsersSolved + "," + results2.AveragePrecision + "," + results2.AverageRecall);
w.WriteLine("SVD," + scores3.RootMeanSquareDifference + "," + results3.TotalUsers + "," + results3.UsersSolved + "," + results3.AveragePrecision + "," + results3.AverageRecall);
w.WriteLine("ICF," + scores4.RootMeanSquareDifference + "," + results4.TotalUsers + "," + results4.UsersSolved + "," + results4.AveragePrecision + "," + results4.AverageRecall);
w.WriteLine("HR," + scores1.RootMeanSquareDifference + "," + results1.TotalUsers + "," + results1.UsersSolved + "," + results1.AveragePrecision + "," + results1.AverageRecall);
}
}
public void RemoveGame(int index)
{
Game game = Games[index];
int winnerScore = 0;
for (int i = 0; i < Players.Count; ++i)
{
int score = ComputeScore(game.NumBomb, GetNumCard(game.NumCards, i));
winnerScore -= score;
Players[i].Score -= score;
}
Players[game.Winner].Score -= winnerScore;
Games.RemoveAt(index);
ScoreResults.RemoveAt(index);
}
public IActionResult GetByUserId()
{
if (!ModelState.IsValid)
{
return(BadRequest());
}
var id = User.Identity.GetUserIdentity();
if (!_board.AllRecords().Any(x => x.UserId == id))
{
return(NotFound());
}
var query = _db.Database.GetCollection <ScoreRecord>(ResourceType.ScoreRecord.Name).AsQueryable();
var allRecords = new ScoreResults(query.Where(x => x.UserId == id)
.OrderByDescending(x => x.Timestamp)
.PaginateAndSelect(null, null, x => new ScoreResult(x)));
allRecords.Rank = _board.AllRecords().ToList().FindIndex(x => x.UserId == id) + 1;
return(Ok(allRecords));
}
private void AddGame(Game game)
{
ScoreResult scoreResult = new ScoreResult();
scoreResult.Time = game.Time;
scoreResult.NumBomb = game.NumBomb;
Object scoreResultBox = scoreResult;
int winnerScore = 0;
for (int i = 0; i < Players.Count; ++i)
{
int score = ComputeScore(game.NumBomb, GetNumCard(game.NumCards, i));
winnerScore -= score;
scoreResult.GetType().GetProperty(string.Format("Score{0}", i)).SetValue(scoreResultBox, score);
Players[i].Score += score;
}
scoreResult.GetType().GetProperty(string.Format("Score{0}", game.Winner)).SetValue(scoreResultBox, winnerScore);
Players[game.Winner].Score += winnerScore;
Games.Add(game);
ScoreResults.Add((ScoreResult)scoreResultBox);
}