Fix typo in time series forecasting API.

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);

src/Microsoft.ML.TimeSeries/ExtensionsCatalog.cs

@@ -164,11 +164,11 @@ public static SrCnnAnomalyEstimator DetectAnomalyBySrCnn(this TransformsCatalog
         /// <param name="rank">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.</param>
         /// <param name="maxRank">The maximum rank considered during the rank selection process. If not provided (i.e. set to null), it is set to windowSize - 1.</param>
-        /// <param name="shouldStablize">The flag determining whether the model should be stabilized.</param>
+        /// <param name="shouldStabilize">The flag determining whether the model should be stabilized.</param>
         /// <param name="shouldMaintainInfo">The flag determining whether the meta information for the model needs to be maintained.</param>
         /// <param name="maxGrowth">The maximum growth on the exponential trend.</param>
-        /// <param name="forcastingConfidentLowerBoundColumnName">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
-        /// <param name="forcastingConfidentUpperBoundColumnName">The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.</param>
+        /// <param name="lowerBoundConfidenceColumn">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
+        /// <param name="upperBoundConfidenceColumn">The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.</param>
         /// <param name="confidenceLevel">The confidence level for forecasting.</param>
         /// <param name="variableHorizon">Set this to true if horizon will change after training(at prediction time).</param>
         /// <example>
@@ -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);
     }
 }

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 : IEstimator<SsaForecastingTransform
         /// <param name="rank">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.</param>
         /// <param name="maxRank">The maximum rank considered during the rank selection process. If not provided (i.e. set to null), it is set to windowSize - 1.</param>
-        /// <param name="shouldStablize">The flag determining whether the model should be stabilized.</param>
+        /// <param name="shouldStabilize">The flag determining whether the model should be stabilized.</param>
         /// <param name="shouldMaintainInfo">The flag determining whether the meta information for the model needs to be maintained.</param>
         /// <param name="maxGrowth">The maximum growth on the exponential trend.</param>
-        /// <param name="forcastingConfidentLowerBoundColumnName">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
-        /// <param name="forcastingConfidentUpperBoundColumnName">The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.</param>
+        /// <param name="lowerBoundConfidenceColumn">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
+        /// <param name="upperBoundConfidenceColumn">The name of the confidence interval upper bound column. If not specified then confidence intervals will not be calculated.</param>
         /// <param name="confidenceLevel">The confidence level for forecasting.</param>
         /// <param name="variableHorizon">Set this to true if horizon will change after training.</param>
         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);
             }
 

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)
         {
         }
 

src/Microsoft.ML.TimeSeries/SsaForecastingBase.cs

@@ -127,16 +127,16 @@ internal sealed class SsaForecastingBase : SequentialForecastingTransformBase<fl
             internal SequenceModelerBase<Single, Single> 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;
                 Horizon = options.Horizon;
                 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();

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,

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);
 

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<TestDataXY> { new TestDataXY() { A = new float[inputSize] } };
             var stringData = new List<TestDataDifferntType> { new TestDataDifferntType() { data_0 = new string[inputSize] } };