public AccuracyEstimates CalculateEstimates(ICollection <Record> records)
        {
            var accuracyEstimates = new AccuracyEstimates();
            var polynomial        = _regressionService.CalculateRegression(records);

            var approximatedPairs = records.Select((record) =>
            {
                double output = 0.0;

                for (int i = 1; i <= record.Inputs.Count; i++)
                {
                    output += record.Inputs.ElementAt(i - 1) * polynomial.ElementAt(i);
                }

                return(new Record
                {
                    Inputs = record.Inputs,
                    Output = output + polynomial.ElementAt(0)
                });
            }).ToArray();

            accuracyEstimates.ApproximationOutputs = approximatedPairs.Select(pair => pair.Output).ToArray();

            accuracyEstimates.SquareSumMax = records.Join(approximatedPairs,
                                                          r => r.Inputs,
                                                          est => est.Inputs,
                                                          (r, est) => new
            {
                DiscreteOutput  = r.Output,
                EstimatedOutput = est.Output
            }).Max(pair => Math.Pow(pair.DiscreteOutput - pair.EstimatedOutput, 2));

            var outputsAvg           = records.Select(record => record.Output).Average();
            var approximatedPairsAvg = approximatedPairs.Select(record => record.Output).Average();

            var outputCov = records
                            .Zip(approximatedPairs, (o, a) => (o.Output - outputsAvg) * (a.Output - approximatedPairsAvg))
                            .Sum();

            var outputDispX = records.Sum(x => Math.Pow(x.Output - outputsAvg, 2));
            var outputDispY = approximatedPairs.Sum(x => Math.Pow(x.Output - approximatedPairsAvg, 2));

            var outputDispMult = Math.Sqrt(outputDispX * outputDispY);

            accuracyEstimates.Correlation = outputCov / outputDispMult;

            return(accuracyEstimates);
        }
        public IActionResult ProcessData([FromBody] DatasetProcessingModel dataset, [FromQuery] int?digits)
        {
            _logger.LogInformation($"[{DateTime.Now}] Params: statistic size: {dataset.Records.Count()}");
            ICollection <double> poly = _regressionService.CalculateRegression(
                dataset.Records.Select(row => new Record
            {
                Inputs = row.Inputs,
                Output = row.Output
            }).ToArray());

            if (digits.HasValue)
            {
                poly = poly.Select(number => Math.Round(number, digits.Value)).ToArray();
            }

            return(Ok(new PolynomialModel {
                Koeficients = poly
            }));
        }
예제 #3
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        public async Task <IActionResult> CalculateEquation(Guid id, [FromQuery] int?digits)
        {
            _logger.LogInformation($"[{DateTime.Now}] Calculate equation for dataset #{id}");
            var dataset = await _datasetService.GetDatasetById(id);

            ICollection <double> poly = _regressionService.CalculateRegression(
                dataset.Records.Select(row => new Record
            {
                Inputs = row.Inputs,
                Output = row.Output
            }).ToArray());

            if (digits.HasValue)
            {
                poly = poly.Select(number => Math.Round(number, digits.Value)).ToArray();
            }

            return(Ok(new PolynomialModel {
                Koeficients = poly
            }));
        }
예제 #4
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        public IActionResult Recommendations()
        {
            var userId = _jwt.GetUserIdFromContext(HttpContext.User);

            if (userId == null)
            {
                return(Unauthorized());
            }

            try
            {
                var player = _context
                             .Players
                             .Include(p => p.Likes)
                             .ThenInclude(l => l.Game)
                             .ThenInclude(g => g.Profile)
                             .ThenInclude(p => p.Conflict)

                             .Include(p => p.Likes)
                             .ThenInclude(l => l.Game)
                             .ThenInclude(g => g.Profile)
                             .ThenInclude(p => p.Agency)

                             .Include(p => p.Likes)
                             .ThenInclude(l => l.Game)
                             .ThenInclude(g => g.Profile)
                             .ThenInclude(p => p.Appearance)

                             .Include(p => p.Likes)
                             .ThenInclude(l => l.Game)
                             .ThenInclude(g => g.Profile)
                             .ThenInclude(p => p.Investment)

                             .Include(p => p.Likes)
                             .ThenInclude(l => l.Game)
                             .ThenInclude(g => g.Profile)
                             .ThenInclude(p => p.Rules)

                             .First(p => p.User.Id == userId);

                var randomNotLikedGames = _context.Games
                                          .FromSql("SELECT TOP (31) * from Games " +
                                                   " WHERE Id NOT IN (SELECT g.Id FROM Games g " +
                                                   "INNER JOIN Likes l ON g.Id = l.GameId " +
                                                   "INNER JOIN Players p ON l.PlayerId = p.Id " +
                                                   "INNER JOIN Users u ON p.Id = u.PlayerId " +
                                                   "WHERE u.Id = {0})", userId)
                                          .Include(g => g.Profile)
                                          .ThenInclude(g => g.Agency)
                                          .Include(g => g.Profile)
                                          .ThenInclude(g => g.Appearance)
                                          .Include(g => g.Profile)
                                          .ThenInclude(g => g.Conflict)
                                          .Include(g => g.Profile)
                                          .ThenInclude(g => g.Investment)
                                          .Include(g => g.Profile)
                                          .ThenInclude(g => g.Rules)
                                          .ToList();

                _regressionService.CalculateRegression(player, randomNotLikedGames);
                _context.SaveChanges();

                var notLikedGames = _context.Games
                                    .FromSql("SELECT * from Games " +
                                             " WHERE Id NOT IN (SELECT g.Id FROM Games g " +
                                             "INNER JOIN Likes l ON g.Id = l.GameId " +
                                             "INNER JOIN Players p ON l.PlayerId = p.Id " +
                                             "INNER JOIN Users u ON p.Id = u.PlayerId " +
                                             "WHERE u.Id = {0})", userId)
                                    .Include(g => g.Profile)
                                    .ThenInclude(g => g.Agency)
                                    .Include(g => g.Profile)
                                    .ThenInclude(g => g.Appearance)
                                    .Include(g => g.Profile)
                                    .ThenInclude(g => g.Conflict)
                                    .Include(g => g.Profile)
                                    .ThenInclude(g => g.Investment)
                                    .Include(g => g.Profile)
                                    .ThenInclude(g => g.Rules)
                                    .ToList();

                var recommendedGames = _regressionService
                                       .OrderGameListByRegressionScore(player, notLikedGames)
                                       .ToArray();

                var recommendations = new long[recommendedGames.Length];
                for (var i = 0; i < recommendedGames.Length; i++)
                {
                    recommendations[i] = recommendedGames[i].Id;
                }

                return(Ok(recommendations));
            }
            catch (Exception e)
            {
                Console.WriteLine(e);
                return(BadRequest(e));
            }
        }