5 writes to _info
Microsoft.ML.TimeSeries (5)
AdaptiveSingularSpectrumSequenceModeler.cs (5)
286_info = new ModelInfo(); 320_info = model._info; 418_info = new ModelInfo(); 1181_info = new ModelInfo(); 1232_info = new ModelInfo();
31 references to _info
Microsoft.ML.TimeSeries (31)
AdaptiveSingularSpectrumSequenceModeler.cs (31)
144get { return _info; } 287_info.WindowSize = _windowSize; 320_info = model._info; 419_info.AutoRegressiveCoefficients = new Single[_windowSize - 1]; 420Array.Copy(_alpha, _info.AutoRegressiveCoefficients, _windowSize - 1); 422_info.IsStabilized = _shouldStablize; 423_info.Rank = _rank; 424_info.WindowSize = _windowSize; 842_info.RootsBeforeStabilization = new[] { new Complex(_alpha[0], 0) }; 851_info.IsStabilized = true; 852_info.RootsAfterStabilization = new[] { new Complex(_alpha[0], 0) }; 853_info.IsExponentialTrendPresent = false; 854_info.IsPolynomialTrendPresent = false; 855_info.ExponentialTrendFactor = Math.Abs(_alpha[0]); 881_info.RootsBeforeStabilization = new Complex[_windowSize - 1]; 882Array.Copy(roots, _info.RootsBeforeStabilization, _windowSize - 1); 921_info.IsArtificialSeasonalityRemoved = true; 1088_info.RootsAfterStabilization = roots; 1089_info.IsStabilized = true; 1090_info.IsPolynomialTrendPresent = polynomialTrendFound; 1091_info.IsExponentialTrendPresent = maxTrendMagnitude > 1; 1092_info.ExponentialTrendFactor = maxTrendMagnitude; 1182_info.WindowSize = _windowSize; 1233_info.WindowSize = _windowSize; 1403_info.IsTrained = true; 1404_info.WindowSize = _windowSize; 1405_info.AutoRegressiveCoefficients = new Single[_windowSize - 1]; 1406Array.Copy(_alpha, _info.AutoRegressiveCoefficients, _windowSize - 1); 1407_info.Rank = _rank; 1408_info.IsNaiveModelTrained = learnNaiveModel; 1409_info.Spectrum = singularVals;