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 f9e7f891f3..c8a3be9305 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,
-                lowerBoundConfidenceColumn: "ConfidenceLowerBound",
-                upperBoundConfidenceColumn: "ConfidenceUpperBound");
+                confidenceLowerBoundColumn: "ConfidenceLowerBound",
+                confidenceUpperBoundColumn: "ConfidenceUpperBound");
 
             // Train.
             var transformer = model.Fit(dataView);
diff --git a/src/Microsoft.ML.TimeSeries/ExtensionsCatalog.cs b/src/Microsoft.ML.TimeSeries/ExtensionsCatalog.cs
index 2581347b3c..11ffa01017 100644
--- a/src/Microsoft.ML.TimeSeries/ExtensionsCatalog.cs
+++ b/src/Microsoft.ML.TimeSeries/ExtensionsCatalog.cs
@@ -167,8 +167,8 @@ public static SrCnnAnomalyEstimator DetectAnomalyBySrCnn(this TransformsCatalog
         /// <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="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="confidenceLowerBoundColumn">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
+        /// <param name="confidenceUpperBoundColumn">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 shouldStabilize = true, bool shouldMaintainInfo = false, GrowthRatio? maxGrowth = null, string lowerBoundConfidenceColumn = null,
-            string upperBoundConfidenceColumn = null, float confidenceLevel = 0.95f, bool variableHorizon = false) =>
+            int? maxRank = null, bool shouldStabilize = true, bool shouldMaintainInfo = false, GrowthRatio? maxGrowth = null, string confidenceLowerBoundColumn = null,
+            string confidenceUpperBoundColumn = null, float confidenceLevel = 0.95f, bool variableHorizon = false) =>
             new SsaForecastingEstimator(CatalogUtils.GetEnvironment(catalog), outputColumnName, inputColumnName, windowSize, seriesLength, trainSize,
-                horizon, isAdaptive, discountFactor, rankSelectionMethod, rank, maxRank, shouldStabilize, shouldMaintainInfo, maxGrowth, lowerBoundConfidenceColumn,
-                upperBoundConfidenceColumn, confidenceLevel, variableHorizon);
+                horizon, isAdaptive, discountFactor, rankSelectionMethod, rank, maxRank, shouldStabilize, shouldMaintainInfo, maxGrowth, confidenceLowerBoundColumn,
+                confidenceUpperBoundColumn, confidenceLevel, variableHorizon);
     }
 }
diff --git a/src/Microsoft.ML.TimeSeries/SSaForecasting.cs b/src/Microsoft.ML.TimeSeries/SSaForecasting.cs
index d6e7f9e8ab..8dc9c981b3 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 LowerBoundConfidenceColumn;
+            public string ConfidenceLowerBoundColumn;
 
             [Argument(ArgumentType.AtMostOnce, HelpText = "The name of the confidence interval upper bound column.", ShortName = "cnfmaxnname", SortOrder = 3)]
-            public string UpperBoundConfidenceColumn;
+            public string ConfidenceUpperBoundColumn;
 
             [Argument(ArgumentType.AtMostOnce, HelpText = "The discount factor in [0,1] used for online updates.", ShortName = "disc", SortOrder = 5)]
             public float DiscountFactor = 1;
@@ -97,8 +97,8 @@ public BaseArguments(Options options)
             {
                 Source = options.Source;
                 Name = options.Name;
-                LowerBoundConfidenceColumn = options.LowerBoundConfidenceColumn;
-                UpperBoundConfidenceColumn = options.UpperBoundConfidenceColumn;
+                ConfidenceLowerBoundColumn = options.ConfidenceLowerBoundColumn;
+                ConfidenceUpperBoundColumn = options.ConfidenceUpperBoundColumn;
                 WindowSize = options.WindowSize;
                 DiscountFactor = options.DiscountFactor;
                 IsAdaptive = options.IsAdaptive;
@@ -258,8 +258,8 @@ public sealed class SsaForecastingEstimator : IEstimator<SsaForecastingTransform
         /// <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="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="confidenceLowerBoundColumn">The name of the confidence interval lower bound column. If not specified then confidence intervals will not be calculated.</param>
+        /// <param name="confidenceUpperBoundColumn">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,
@@ -277,8 +277,8 @@ internal SsaForecastingEstimator(IHostEnvironment env,
             bool shouldStabilize = true,
             bool shouldMaintainInfo = false,
             GrowthRatio? maxGrowth = null,
-            string lowerBoundConfidenceColumn = null,
-            string upperBoundConfidenceColumn = null,
+            string confidenceLowerBoundColumn = null,
+            string confidenceUpperBoundColumn = null,
             float confidenceLevel = 0.95f,
             bool variableHorizon = false)
             : this(env, new SsaForecastingTransformer.Options
@@ -295,8 +295,8 @@ internal SsaForecastingEstimator(IHostEnvironment env,
                 ShouldMaintainInfo = shouldMaintainInfo,
                 MaxGrowth = maxGrowth,
                 ConfidenceLevel = confidenceLevel,
-                LowerBoundConfidenceColumn = lowerBoundConfidenceColumn,
-                UpperBoundConfidenceColumn = upperBoundConfidenceColumn,
+                ConfidenceLowerBoundColumn = confidenceLowerBoundColumn,
+                ConfidenceUpperBoundColumn = confidenceUpperBoundColumn,
                 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.UpperBoundConfidenceColumn))
+            if (!string.IsNullOrEmpty(_options.ConfidenceUpperBoundColumn))
             {
-                resultDic[_options.LowerBoundConfidenceColumn] = new SchemaShape.Column(
-                    _options.LowerBoundConfidenceColumn, SchemaShape.Column.VectorKind.Vector,
+                resultDic[_options.ConfidenceLowerBoundColumn] = new SchemaShape.Column(
+                    _options.ConfidenceLowerBoundColumn, SchemaShape.Column.VectorKind.Vector,
                     NumberDataViewType.Single, false);
 
-                resultDic[_options.UpperBoundConfidenceColumn] = new SchemaShape.Column(
-                    _options.UpperBoundConfidenceColumn, SchemaShape.Column.VectorKind.Vector,
+                resultDic[_options.ConfidenceUpperBoundColumn] = new SchemaShape.Column(
+                    _options.ConfidenceUpperBoundColumn, SchemaShape.Column.VectorKind.Vector,
                     NumberDataViewType.Single, false);
             }
 
diff --git a/src/Microsoft.ML.TimeSeries/SequentialForecastingTransformBase.cs b/src/Microsoft.ML.TimeSeries/SequentialForecastingTransformBase.cs
index 4f1e96039c..5b7813bc11 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 LowerBoundConfidenceColumn;
+        public string ConfidenceLowerBoundColumn;
 
         [Argument(ArgumentType.Required, HelpText = "The name of the confidence interval upper bound column.", ShortName = "cnfmaxnname",
             SortOrder = 2)]
-        public string UpperBoundConfidenceColumn;
+        public string ConfidenceUpperBoundColumn;
 
         [Argument(ArgumentType.AtMostOnce, HelpText = "The length of series from the begining used for training.", ShortName = "wnd",
             SortOrder = 3)]
@@ -57,18 +57,18 @@ internal abstract class SequentialForecastingTransformBase<TInput, TState> : Seq
         private readonly int _outputLength;
 
         private protected SequentialForecastingTransformBase(int windowSize, int initialWindowSize,
-            string inputColumnName, string outputColumnName, string forecastingConfidenceIntervalMinOutputColumnName,
-                string forecastingConfidenceIntervalMaxOutputColumnName, string name, int outputLength, IHostEnvironment env)
+            string inputColumnName, string outputColumnName, string confidenceLowerBoundColumn,
+                string confidenceUpperBoundColumn, string name, int outputLength, IHostEnvironment env)
             : base(Contracts.CheckRef(env, nameof(env)).Register(name), windowSize, initialWindowSize,
-                  outputColumnName, forecastingConfidenceIntervalMinOutputColumnName,
-                  forecastingConfidenceIntervalMaxOutputColumnName, inputColumnName, new VectorDataViewType(NumberDataViewType.Single, outputLength))
+                  outputColumnName, confidenceLowerBoundColumn,
+                  confidenceUpperBoundColumn, inputColumnName, new VectorDataViewType(NumberDataViewType.Single, outputLength))
         {
             _outputLength = outputLength;
         }
 
         private protected SequentialForecastingTransformBase(ForecastingArgumentsBase args, string name, int outputLength, IHostEnvironment env)
-            : this(args.TrainSize, args.SeriesLength, args.Source, args.LowerBoundConfidenceColumn,
-                  args.UpperBoundConfidenceColumn, args.Name, name, outputLength, env)
+            : this(args.TrainSize, args.SeriesLength, args.Source, args.ConfidenceLowerBoundColumn,
+                  args.ConfidenceUpperBoundColumn, args.Name, name, outputLength, env)
         {
         }
 
@@ -127,12 +127,12 @@ public DataViewSchema.DetachedColumn[] GetOutputColumns()
             {
                 DetachedColumn[] info;
 
-                if (!string.IsNullOrEmpty(_parent.ForecastingConfidenceIntervalMaxOutputColumnName))
+                if (!string.IsNullOrEmpty(_parent.ConfidenceUpperBoundColumn))
                 {
                     info = new DetachedColumn[3];
                     info[0] = new DetachedColumn(_parent.OutputColumnName, new VectorDataViewType(NumberDataViewType.Single, _parent._outputLength));
-                    info[1] = new DetachedColumn(_parent.ForecastingConfidenceIntervalMinOutputColumnName, new VectorDataViewType(NumberDataViewType.Single, _parent._outputLength));
-                    info[2] = new DetachedColumn(_parent.ForecastingConfidenceIntervalMaxOutputColumnName, new VectorDataViewType(NumberDataViewType.Single, _parent._outputLength));
+                    info[1] = new DetachedColumn(_parent.ConfidenceLowerBoundColumn, new VectorDataViewType(NumberDataViewType.Single, _parent._outputLength));
+                    info[2] = new DetachedColumn(_parent.ConfidenceUpperBoundColumn, new VectorDataViewType(NumberDataViewType.Single, _parent._outputLength));
                 }
                 else
                 {
@@ -156,7 +156,7 @@ public Func<int, bool> GetDependencies(Func<int, bool> activeOutput)
             public Delegate[] CreateGetters(DataViewRow input, Func<int, bool> activeOutput, out Action disposer)
             {
                 disposer = null;
-                var getters = string.IsNullOrEmpty(_parent.ForecastingConfidenceIntervalMaxOutputColumnName) ? new Delegate[1] : new Delegate[3];
+                var getters = string.IsNullOrEmpty(_parent.ConfidenceUpperBoundColumn) ? new Delegate[1] : new Delegate[3];
 
                 if (activeOutput(0))
                 {
@@ -168,7 +168,7 @@ public Delegate[] CreateGetters(DataViewRow input, Func<int, bool> activeOutput,
                     getters[0] = valueGetter;
                 }
 
-                if (!string.IsNullOrEmpty(_parent.ForecastingConfidenceIntervalMaxOutputColumnName))
+                if (!string.IsNullOrEmpty(_parent.ConfidenceUpperBoundColumn))
                 {
                     if (activeOutput(1))
                     {
diff --git a/src/Microsoft.ML.TimeSeries/SequentialTransformerBase.cs b/src/Microsoft.ML.TimeSeries/SequentialTransformerBase.cs
index af6017a6ca..4ffe27b31f 100644
--- a/src/Microsoft.ML.TimeSeries/SequentialTransformerBase.cs
+++ b/src/Microsoft.ML.TimeSeries/SequentialTransformerBase.cs
@@ -335,8 +335,8 @@ private protected virtual void CloneCore(TState state)
 
         internal readonly string InputColumnName;
         internal readonly string OutputColumnName;
-        internal readonly string ForecastingConfidenceIntervalMinOutputColumnName;
-        internal readonly string ForecastingConfidenceIntervalMaxOutputColumnName;
+        internal readonly string ConfidenceLowerBoundColumn;
+        internal readonly string ConfidenceUpperBoundColumn;
         private protected DataViewType OutputColumnType;
 
         bool ITransformer.IsRowToRowMapper => false;
@@ -372,12 +372,12 @@ private protected SequentialTransformerBase(IHost host, int windowSize, int init
         }
 
         private protected SequentialTransformerBase(IHost host, int windowSize, int initialWindowSize,
-            string outputColumnName, string forecastingConfidenceIntervalMinOutputColumnName,
-            string forecastingConfidenceIntervalMaxOutputColumnName, string inputColumnName, DataViewType outputColType) :
+            string outputColumnName, string confidenceLowerBoundColumn,
+            string confidenceUpperBoundColumn, string inputColumnName, DataViewType outputColType) :
             this(host, windowSize, initialWindowSize, outputColumnName, inputColumnName, outputColType)
         {
-            ForecastingConfidenceIntervalMinOutputColumnName = forecastingConfidenceIntervalMinOutputColumnName;
-            ForecastingConfidenceIntervalMaxOutputColumnName = forecastingConfidenceIntervalMaxOutputColumnName;
+            ConfidenceLowerBoundColumn = confidenceLowerBoundColumn;
+            ConfidenceUpperBoundColumn = confidenceUpperBoundColumn;
         }
 
         private protected SequentialTransformerBase(IHost host, ModelLoadContext ctx)
@@ -403,8 +403,8 @@ private protected SequentialTransformerBase(IHost host, ModelLoadContext ctx)
 
             InputColumnName = inputColumnName;
             OutputColumnName = outputColumnName;
-            ForecastingConfidenceIntervalMinOutputColumnName = ctx.Reader.ReadString();
-            ForecastingConfidenceIntervalMaxOutputColumnName = ctx.Reader.ReadString();
+            ConfidenceLowerBoundColumn = ctx.Reader.ReadString();
+            ConfidenceUpperBoundColumn = ctx.Reader.ReadString();
             InitialWindowSize = initialWindowSize;
             WindowSize = windowSize;
 
@@ -431,8 +431,8 @@ private protected virtual void SaveModel(ModelSaveContext ctx)
             ctx.Writer.Write(InitialWindowSize);
             ctx.SaveNonEmptyString(InputColumnName);
             ctx.SaveNonEmptyString(OutputColumnName);
-            ctx.Writer.Write(ForecastingConfidenceIntervalMinOutputColumnName ?? string.Empty);
-            ctx.Writer.Write(ForecastingConfidenceIntervalMaxOutputColumnName ?? string.Empty);
+            ctx.Writer.Write(ConfidenceLowerBoundColumn ?? string.Empty);
+            ctx.Writer.Write(ConfidenceUpperBoundColumn ?? string.Empty);
             var bs = new BinarySaver(Host, new BinarySaver.Arguments());
             bs.TryWriteTypeDescription(ctx.Writer.BaseStream, OutputColumnType, out int byteWritten);
         }
@@ -480,8 +480,8 @@ public SequentialDataTransform(IHost host, SequentialTransformerBase<TInput, TOu
                 Metadata = new MetadataDispatcher(3);
                 _parent = parent;
                 _transform = CreateLambdaTransform(_parent.Host, input, _parent.InputColumnName,
-                    _parent.OutputColumnName, _parent.ForecastingConfidenceIntervalMinOutputColumnName,
-                    _parent.ForecastingConfidenceIntervalMaxOutputColumnName, InitFunction, _parent.WindowSize > 0, _parent.OutputColumnType);
+                    _parent.OutputColumnName, _parent.ConfidenceLowerBoundColumn,
+                    _parent.ConfidenceUpperBoundColumn, InitFunction, _parent.WindowSize > 0, _parent.OutputColumnType);
 
                 _mapper = mapper;
                 _bindings = new ColumnBindings(input.Schema, _mapper.GetOutputColumns());
diff --git a/src/Microsoft.ML.TimeSeries/SsaForecastingBase.cs b/src/Microsoft.ML.TimeSeries/SsaForecastingBase.cs
index f7911e1047..1eb942c775 100644
--- a/src/Microsoft.ML.TimeSeries/SsaForecastingBase.cs
+++ b/src/Microsoft.ML.TimeSeries/SsaForecastingBase.cs
@@ -127,8 +127,8 @@ 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.LowerBoundConfidenceColumn,
-                      options.UpperBoundConfidenceColumn, name, options.VariableHorizon ? 0: options.Horizon, env)
+                : base(options.TrainSize, 0, options.Source, options.Name, options.ConfidenceLowerBoundColumn,
+                      options.ConfidenceUpperBoundColumn, 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.LowerBoundConfidenceColumn),
+                    options.DiscountFactor, options.RankSelectionMethod, options.Rank, options.MaxRank, !string.IsNullOrEmpty(options.ConfidenceLowerBoundColumn),
                     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 166e75173b..6d9e968d58 100644
--- a/test/BaselineOutput/Common/EntryPoints/core_manifest.json
+++ b/test/BaselineOutput/Common/EntryPoints/core_manifest.json
@@ -4095,7 +4095,7 @@
           "Default": false
         },
         {
-          "Name": "LowerBoundConfidenceColumn",
+          "Name": "ConfidenceLowerBoundColumn",
           "Type": "String",
           "Desc": "The name of the confidence interval lower bound column.",
           "Aliases": [
@@ -4107,7 +4107,7 @@
           "Default": null
         },
         {
-          "Name": "UpperBoundConfidenceColumn",
+          "Name": "ConfidenceUpperBoundColumn",
           "Type": "String",
           "Desc": "The name of the confidence interval upper bound column.",
           "Aliases": [
diff --git a/test/Microsoft.ML.TimeSeries.Tests/TimeSeriesDirectApi.cs b/test/Microsoft.ML.TimeSeries.Tests/TimeSeriesDirectApi.cs
index 00b8ec6613..85bac94fff 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",
-                LowerBoundConfidenceColumn = "MinCnf",
-                UpperBoundConfidenceColumn = "MaxCnf",
+                ConfidenceLowerBoundColumn = "MinCnf",
+                ConfidenceUpperBoundColumn = "MaxCnf",
                 WindowSize = 10,
                 SeriesLength = 11,
                 TrainSize = 22,
@@ -397,8 +397,8 @@ public void SsaForecastPredictionEngine()
                 SeriesLength = 11,
                 TrainSize = 22,
                 Horizon = 4,
-                LowerBoundConfidenceColumn = "ConfidenceLowerBound",
-                UpperBoundConfidenceColumn = "ConfidenceUpperBound",
+                ConfidenceLowerBoundColumn = "ConfidenceLowerBound",
+                ConfidenceUpperBoundColumn = "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,
-                    lowerBoundConfidenceColumn: "ConfidenceLowerBound",
-                    upperBoundConfidenceColumn: "ConfidenceUpperBound", variableHorizon: true))
+                    confidenceLowerBoundColumn: "ConfidenceLowerBound",
+                    confidenceUpperBoundColumn: "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 ee1b40156e..d9fe04bccd 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,
-                    lowerBoundConfidenceColumn: "ConfidenceLowerBound",
-                    upperBoundConfidenceColumn: "ConfidenceUpperBound");
+                    confidenceLowerBoundColumn: "ConfidenceLowerBound",
+                    confidenceUpperBoundColumn: "ConfidenceUpperBound");
 
             var xyData = new List<TestDataXY> { new TestDataXY() { A = new float[inputSize] } };
             var stringData = new List<TestDataDifferntType> { new TestDataDifferntType() { data_0 = new string[inputSize] } };