diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/TimeSeries/ForecastingWithConfidenceInterval.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/TimeSeries/ForecastingWithConfidenceInterval.cs
index 571cf9325a..f9e7f891f3 100644
--- a/docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/TimeSeries/ForecastingWithConfidenceInterval.cs
+++ b/docs/samples/Microsoft.ML.Samples/Dynamic/Transforms/TimeSeries/ForecastingWithConfidenceInterval.cs
@@ -48,8 +48,8 @@ public static void Example()
// Instantiate the forecasting model.
var model = ml.Forecasting.ForecastBySsa(outputColumnName, inputColumnName, 5, 11, data.Count, 5,
confidenceLevel: 0.95f,
- forcastingConfidentLowerBoundColumnName: "ConfidenceLowerBound",
- forcastingConfidentUpperBoundColumnName: "ConfidenceUpperBound");
+ lowerBoundConfidenceColumn: "ConfidenceLowerBound",
+ upperBoundConfidenceColumn: "ConfidenceUpperBound");
// Train.
var transformer = model.Fit(dataView);
diff --git a/src/Microsoft.ML.TimeSeries/ExtensionsCatalog.cs b/src/Microsoft.ML.TimeSeries/ExtensionsCatalog.cs
index bfec448467..2581347b3c 100644
--- a/src/Microsoft.ML.TimeSeries/ExtensionsCatalog.cs
+++ b/src/Microsoft.ML.TimeSeries/ExtensionsCatalog.cs
@@ -164,11 +164,11 @@ public static SrCnnAnomalyEstimator DetectAnomalyBySrCnn(this TransformsCatalog
/// The desired rank of the subspace used for SSA projection (parameter r). This parameter should be in the range in [1, windowSize].
/// If set to null, the rank is automatically determined based on prediction error minimization.
/// The maximum rank considered during the rank selection process. If not provided (i.e. set to null), it is set to windowSize - 1.
- /// The flag determining whether the model should be stabilized.
+ /// The flag determining whether the model should be stabilized.
/// The flag determining whether the meta information for the model needs to be maintained.
/// The maximum growth on the exponential trend.
- /// The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.
- /// The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.
+ /// The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.
+ /// The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.
/// The confidence level for forecasting.
/// Set this to true if horizon will change after training(at prediction time).
///
@@ -182,10 +182,10 @@ public static SrCnnAnomalyEstimator DetectAnomalyBySrCnn(this TransformsCatalog
public static SsaForecastingEstimator ForecastBySsa(
this ForecastingCatalog catalog, string outputColumnName, string inputColumnName, int windowSize, int seriesLength, int trainSize, int horizon,
bool isAdaptive = false, float discountFactor = 1, RankSelectionMethod rankSelectionMethod = RankSelectionMethod.Exact, int? rank = null,
- int? maxRank = null, bool shouldStablize = true, bool shouldMaintainInfo = false, GrowthRatio? maxGrowth = null, string forcastingConfidentLowerBoundColumnName = null,
- string forcastingConfidentUpperBoundColumnName = null, float confidenceLevel = 0.95f, bool variableHorizon = false) =>
+ int? maxRank = null, bool shouldStabilize = true, bool shouldMaintainInfo = false, GrowthRatio? maxGrowth = null, string lowerBoundConfidenceColumn = null,
+ string upperBoundConfidenceColumn = null, float confidenceLevel = 0.95f, bool variableHorizon = false) =>
new SsaForecastingEstimator(CatalogUtils.GetEnvironment(catalog), outputColumnName, inputColumnName, windowSize, seriesLength, trainSize,
- horizon, isAdaptive, discountFactor, rankSelectionMethod, rank, maxRank, shouldStablize, shouldMaintainInfo, maxGrowth, forcastingConfidentLowerBoundColumnName,
- forcastingConfidentUpperBoundColumnName, confidenceLevel, variableHorizon);
+ horizon, isAdaptive, discountFactor, rankSelectionMethod, rank, maxRank, shouldStabilize, shouldMaintainInfo, maxGrowth, lowerBoundConfidenceColumn,
+ upperBoundConfidenceColumn, confidenceLevel, variableHorizon);
}
}
diff --git a/src/Microsoft.ML.TimeSeries/SSaForecasting.cs b/src/Microsoft.ML.TimeSeries/SSaForecasting.cs
index ab8684c147..d6e7f9e8ab 100644
--- a/src/Microsoft.ML.TimeSeries/SSaForecasting.cs
+++ b/src/Microsoft.ML.TimeSeries/SSaForecasting.cs
@@ -42,10 +42,10 @@ internal sealed class Options : TransformInputBase
public string Name;
[Argument(ArgumentType.AtMostOnce, HelpText = "The name of the confidence interval lower bound column.", ShortName = "cnfminname", SortOrder = 3)]
- public string ForcastingConfidentLowerBoundColumnName;
+ public string LowerBoundConfidenceColumn;
[Argument(ArgumentType.AtMostOnce, HelpText = "The name of the confidence interval upper bound column.", ShortName = "cnfmaxnname", SortOrder = 3)]
- public string ForcastingConfidentUpperBoundColumnName;
+ public string UpperBoundConfidenceColumn;
[Argument(ArgumentType.AtMostOnce, HelpText = "The discount factor in [0,1] used for online updates.", ShortName = "disc", SortOrder = 5)]
public float DiscountFactor = 1;
@@ -67,7 +67,7 @@ internal sealed class Options : TransformInputBase
public int? MaxRank = null;
[Argument(ArgumentType.AtMostOnce, HelpText = "The flag determining whether the model should be stabilized.", SortOrder = 3)]
- public bool ShouldStablize = true;
+ public bool ShouldStabilize = true;
[Argument(ArgumentType.AtMostOnce, HelpText = "The flag determining whether the meta information for the model needs to be maintained.", SortOrder = 3)]
public bool ShouldMaintainInfo = false;
@@ -97,14 +97,14 @@ public BaseArguments(Options options)
{
Source = options.Source;
Name = options.Name;
- ForcastingConfidentLowerBoundColumnName = options.ForcastingConfidentLowerBoundColumnName;
- ForcastingConfidentUpperBoundColumnName = options.ForcastingConfidentUpperBoundColumnName;
+ LowerBoundConfidenceColumn = options.LowerBoundConfidenceColumn;
+ UpperBoundConfidenceColumn = options.UpperBoundConfidenceColumn;
WindowSize = options.WindowSize;
DiscountFactor = options.DiscountFactor;
IsAdaptive = options.IsAdaptive;
RankSelectionMethod = options.RankSelectionMethod;
Rank = options.Rank;
- ShouldStablize = options.ShouldStablize;
+ ShouldStablize = options.ShouldStabilize;
MaxGrowth = options.MaxGrowth;
SeriesLength = options.SeriesLength;
TrainSize = options.TrainSize;
@@ -255,11 +255,11 @@ public sealed class SsaForecastingEstimator : IEstimatorThe desired rank of the subspace used for SSA projection (parameter r). This parameter should be in the range in [1, windowSize].
/// If set to null, the rank is automatically determined based on prediction error minimization.
/// The maximum rank considered during the rank selection process. If not provided (i.e. set to null), it is set to windowSize - 1.
- /// The flag determining whether the model should be stabilized.
+ /// The flag determining whether the model should be stabilized.
/// The flag determining whether the meta information for the model needs to be maintained.
/// The maximum growth on the exponential trend.
- /// The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.
- /// The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.
+ /// The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.
+ /// The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.
/// The confidence level for forecasting.
/// Set this to true if horizon will change after training.
internal SsaForecastingEstimator(IHostEnvironment env,
@@ -274,11 +274,11 @@ internal SsaForecastingEstimator(IHostEnvironment env,
RankSelectionMethod rankSelectionMethod = RankSelectionMethod.Exact,
int? rank = null,
int? maxRank = null,
- bool shouldStablize = true,
+ bool shouldStabilize = true,
bool shouldMaintainInfo = false,
GrowthRatio? maxGrowth = null,
- string forcastingConfidentLowerBoundColumnName = null,
- string forcastingConfidentUpperBoundColumnName = null,
+ string lowerBoundConfidenceColumn = null,
+ string upperBoundConfidenceColumn = null,
float confidenceLevel = 0.95f,
bool variableHorizon = false)
: this(env, new SsaForecastingTransformer.Options
@@ -291,12 +291,12 @@ internal SsaForecastingEstimator(IHostEnvironment env,
RankSelectionMethod = rankSelectionMethod,
Rank = rank,
MaxRank = maxRank,
- ShouldStablize = shouldStablize,
+ ShouldStabilize = shouldStabilize,
ShouldMaintainInfo = shouldMaintainInfo,
MaxGrowth = maxGrowth,
ConfidenceLevel = confidenceLevel,
- ForcastingConfidentLowerBoundColumnName = forcastingConfidentLowerBoundColumnName,
- ForcastingConfidentUpperBoundColumnName = forcastingConfidentUpperBoundColumnName,
+ LowerBoundConfidenceColumn = lowerBoundConfidenceColumn,
+ UpperBoundConfidenceColumn = upperBoundConfidenceColumn,
SeriesLength = seriesLength,
TrainSize = trainSize,
VariableHorizon = variableHorizon,
@@ -344,14 +344,14 @@ public SchemaShape GetOutputSchema(SchemaShape inputSchema)
resultDic[_options.Name] = new SchemaShape.Column(
_options.Name, SchemaShape.Column.VectorKind.Vector, NumberDataViewType.Single, false);
- if (!string.IsNullOrEmpty(_options.ForcastingConfidentUpperBoundColumnName))
+ if (!string.IsNullOrEmpty(_options.UpperBoundConfidenceColumn))
{
- resultDic[_options.ForcastingConfidentLowerBoundColumnName] = new SchemaShape.Column(
- _options.ForcastingConfidentLowerBoundColumnName, SchemaShape.Column.VectorKind.Vector,
+ resultDic[_options.LowerBoundConfidenceColumn] = new SchemaShape.Column(
+ _options.LowerBoundConfidenceColumn, SchemaShape.Column.VectorKind.Vector,
NumberDataViewType.Single, false);
- resultDic[_options.ForcastingConfidentUpperBoundColumnName] = new SchemaShape.Column(
- _options.ForcastingConfidentUpperBoundColumnName, SchemaShape.Column.VectorKind.Vector,
+ resultDic[_options.UpperBoundConfidenceColumn] = new SchemaShape.Column(
+ _options.UpperBoundConfidenceColumn, SchemaShape.Column.VectorKind.Vector,
NumberDataViewType.Single, false);
}
diff --git a/src/Microsoft.ML.TimeSeries/SequentialForecastingTransformBase.cs b/src/Microsoft.ML.TimeSeries/SequentialForecastingTransformBase.cs
index 27557df7de..4f1e96039c 100644
--- a/src/Microsoft.ML.TimeSeries/SequentialForecastingTransformBase.cs
+++ b/src/Microsoft.ML.TimeSeries/SequentialForecastingTransformBase.cs
@@ -28,11 +28,11 @@ internal abstract class ForecastingArgumentsBase
[Argument(ArgumentType.Required, HelpText = "The name of the confidence interval lower bound column.", ShortName = "cnfminname",
SortOrder = 2)]
- public string ForcastingConfidentLowerBoundColumnName;
+ public string LowerBoundConfidenceColumn;
[Argument(ArgumentType.Required, HelpText = "The name of the confidence interval upper bound column.", ShortName = "cnfmaxnname",
SortOrder = 2)]
- public string ForcastingConfidentUpperBoundColumnName;
+ public string UpperBoundConfidenceColumn;
[Argument(ArgumentType.AtMostOnce, HelpText = "The length of series from the begining used for training.", ShortName = "wnd",
SortOrder = 3)]
@@ -67,8 +67,8 @@ private protected SequentialForecastingTransformBase(int windowSize, int initial
}
private protected SequentialForecastingTransformBase(ForecastingArgumentsBase args, string name, int outputLength, IHostEnvironment env)
- : this(args.TrainSize, args.SeriesLength, args.Source, args.ForcastingConfidentLowerBoundColumnName,
- args.ForcastingConfidentUpperBoundColumnName, args.Name, name, outputLength, env)
+ : this(args.TrainSize, args.SeriesLength, args.Source, args.LowerBoundConfidenceColumn,
+ args.UpperBoundConfidenceColumn, args.Name, name, outputLength, env)
{
}
diff --git a/src/Microsoft.ML.TimeSeries/SsaForecastingBase.cs b/src/Microsoft.ML.TimeSeries/SsaForecastingBase.cs
index 86a48781c7..f7911e1047 100644
--- a/src/Microsoft.ML.TimeSeries/SsaForecastingBase.cs
+++ b/src/Microsoft.ML.TimeSeries/SsaForecastingBase.cs
@@ -127,8 +127,8 @@ internal sealed class SsaForecastingBase : SequentialForecastingTransformBase Model;
public SsaForecastingBase(SsaForecastingOptions options, string name, IHostEnvironment env, SsaForecastingBaseWrapper parent)
- : base(options.TrainSize, 0, options.Source, options.Name, options.ForcastingConfidentLowerBoundColumnName,
- options.ForcastingConfidentUpperBoundColumnName, name, options.VariableHorizon ? 0: options.Horizon, env)
+ : base(options.TrainSize, 0, options.Source, options.Name, options.LowerBoundConfidenceColumn,
+ options.UpperBoundConfidenceColumn, name, options.VariableHorizon ? 0: options.Horizon, env)
{
Host.CheckUserArg(0 <= options.DiscountFactor && options.DiscountFactor <= 1, nameof(options.DiscountFactor), "Must be in the range [0, 1].");
IsAdaptive = options.IsAdaptive;
@@ -136,7 +136,7 @@ public SsaForecastingBase(SsaForecastingOptions options, string name, IHostEnvir
ConfidenceLevel = options.ConfidenceLevel;
// Creating the master SSA model
Model = new AdaptiveSingularSpectrumSequenceModelerInternal(Host, options.TrainSize, options.SeriesLength, options.WindowSize,
- options.DiscountFactor, options.RankSelectionMethod, options.Rank, options.MaxRank, !string.IsNullOrEmpty(options.ForcastingConfidentLowerBoundColumnName),
+ options.DiscountFactor, options.RankSelectionMethod, options.Rank, options.MaxRank, !string.IsNullOrEmpty(options.LowerBoundConfidenceColumn),
options.ShouldStablize, options.ShouldMaintainInfo, options.MaxGrowth);
StateRef = new State();
diff --git a/test/BaselineOutput/Common/EntryPoints/core_manifest.json b/test/BaselineOutput/Common/EntryPoints/core_manifest.json
index c5a734b6b3..166e75173b 100644
--- a/test/BaselineOutput/Common/EntryPoints/core_manifest.json
+++ b/test/BaselineOutput/Common/EntryPoints/core_manifest.json
@@ -4095,7 +4095,7 @@
"Default": false
},
{
- "Name": "ForcastingConfidentLowerBoundColumnName",
+ "Name": "LowerBoundConfidenceColumn",
"Type": "String",
"Desc": "The name of the confidence interval lower bound column.",
"Aliases": [
@@ -4107,7 +4107,7 @@
"Default": null
},
{
- "Name": "ForcastingConfidentUpperBoundColumnName",
+ "Name": "UpperBoundConfidenceColumn",
"Type": "String",
"Desc": "The name of the confidence interval upper bound column.",
"Aliases": [
@@ -4153,7 +4153,7 @@
"Default": null
},
{
- "Name": "ShouldStablize",
+ "Name": "ShouldStabilize",
"Type": "Bool",
"Desc": "The flag determining whether the model should be stabilized.",
"Required": false,
diff --git a/test/Microsoft.ML.TimeSeries.Tests/TimeSeriesDirectApi.cs b/test/Microsoft.ML.TimeSeries.Tests/TimeSeriesDirectApi.cs
index d8f4387d75..00b8ec6613 100644
--- a/test/Microsoft.ML.TimeSeries.Tests/TimeSeriesDirectApi.cs
+++ b/test/Microsoft.ML.TimeSeries.Tests/TimeSeriesDirectApi.cs
@@ -338,8 +338,8 @@ public void SsaForecast()
ConfidenceLevel = 0.95f,
Source = "Value",
Name = "Forecast",
- ForcastingConfidentLowerBoundColumnName = "MinCnf",
- ForcastingConfidentUpperBoundColumnName = "MaxCnf",
+ LowerBoundConfidenceColumn = "MinCnf",
+ UpperBoundConfidenceColumn = "MaxCnf",
WindowSize = 10,
SeriesLength = 11,
TrainSize = 22,
@@ -397,8 +397,8 @@ public void SsaForecastPredictionEngine()
SeriesLength = 11,
TrainSize = 22,
Horizon = 4,
- ForcastingConfidentLowerBoundColumnName = "ConfidenceLowerBound",
- ForcastingConfidentUpperBoundColumnName = "ConfidenceUpperBound",
+ LowerBoundConfidenceColumn = "ConfidenceLowerBound",
+ UpperBoundConfidenceColumn = "ConfidenceUpperBound",
VariableHorizon = true
};
@@ -413,8 +413,8 @@ public void SsaForecastPredictionEngine()
var model = ml.Transforms.Text.FeaturizeText("Text_Featurized", "Text")
.Append(ml.Transforms.Conversion.ConvertType("Value", "Value", DataKind.Single))
.Append(ml.Forecasting.ForecastBySsa("Forecast", "Value", 10, 11, 22, 4,
- forcastingConfidentLowerBoundColumnName: "ConfidenceLowerBound",
- forcastingConfidentUpperBoundColumnName: "ConfidenceUpperBound", variableHorizon: true))
+ lowerBoundConfidenceColumn: "ConfidenceLowerBound",
+ upperBoundConfidenceColumn: "ConfidenceUpperBound", variableHorizon: true))
.Append(ml.Transforms.Concatenate("Forecast", "Forecast", "ConfidenceLowerBound", "ConfidenceUpperBound"))
.Fit(dataView);
diff --git a/test/Microsoft.ML.TimeSeries.Tests/TimeSeriesEstimatorTests.cs b/test/Microsoft.ML.TimeSeries.Tests/TimeSeriesEstimatorTests.cs
index efb25b43e3..ee1b40156e 100644
--- a/test/Microsoft.ML.TimeSeries.Tests/TimeSeriesEstimatorTests.cs
+++ b/test/Microsoft.ML.TimeSeries.Tests/TimeSeriesEstimatorTests.cs
@@ -95,8 +95,8 @@ void TestSsaForecastingEstimator()
// Train
var pipe = new SsaForecastingEstimator(Env, "Forecast", "Value", 10, 11, 22, 4,
- forcastingConfidentLowerBoundColumnName: "ConfidenceLowerBound",
- forcastingConfidentUpperBoundColumnName: "ConfidenceUpperBound");
+ lowerBoundConfidenceColumn: "ConfidenceLowerBound",
+ upperBoundConfidenceColumn: "ConfidenceUpperBound");
var xyData = new List { new TestDataXY() { A = new float[inputSize] } };
var stringData = new List { new TestDataDifferntType() { data_0 = new string[inputSize] } };