lightgbm fact

Author: artidoro

test/Microsoft.ML.Tests/TrainerEstimators/TreeEstimators.cs

@@ -23,7 +23,7 @@ namespace Microsoft.ML.Tests.TrainerEstimators
     public partial class TrainerEstimators : TestDataPipeBase
     {
         /// <summary>
-        /// FastTreeBinaryClassification TrainerEstimator test 
+        /// FastTreeBinaryClassification TrainerEstimator test
         /// </summary>
         [Fact]
         public void FastTreeBinaryEstimator()
@@ -67,7 +67,7 @@ public void LightGBMBinaryEstimator()
         }
 
         /// <summary>
-        /// LightGBMBinaryTrainer CorrectSigmoid test 
+        /// LightGBMBinaryTrainer CorrectSigmoid test
         /// </summary>
         [LightGBMFact]
         public void LightGBMBinaryEstimatorCorrectSigmoid()
@@ -132,7 +132,7 @@ public void FastForestClassificationEstimator()
         }
 
         /// <summary>
-        /// FastTreeRankingTrainer TrainerEstimator test 
+        /// FastTreeRankingTrainer TrainerEstimator test
         /// </summary>
         [Fact]
         public void FastTreeRankerEstimator()
@@ -156,7 +156,7 @@ public void FastTreeRankerEstimator()
         }
 
         /// <summary>
-        /// LightGbmRankingTrainer TrainerEstimator test 
+        /// LightGbmRankingTrainer TrainerEstimator test
         /// </summary>
         [LightGBMFact]
         public void LightGBMRankerEstimator()
@@ -174,7 +174,7 @@ public void LightGBMRankerEstimator()
         }
 
         /// <summary>
-        /// FastTreeRegressor TrainerEstimator test 
+        /// FastTreeRegressor TrainerEstimator test
         /// </summary>
         [Fact]
         public void FastTreeRegressorEstimator()
@@ -189,7 +189,7 @@ public void FastTreeRegressorEstimator()
         }
 
         /// <summary>
-        /// LightGbmRegressionTrainer TrainerEstimator test 
+        /// LightGbmRegressionTrainer TrainerEstimator test
         /// </summary>
         [LightGBMFact]
         public void LightGBMRegressorEstimator()
@@ -209,7 +209,7 @@ public void LightGBMRegressorEstimator()
 
 
         /// <summary>
-        /// RegressionGamTrainer TrainerEstimator test 
+        /// RegressionGamTrainer TrainerEstimator test
         /// </summary>
         [Fact]
         public void GAMRegressorEstimator()
@@ -227,7 +227,7 @@ public void GAMRegressorEstimator()
         }
 
         /// <summary>
-        /// FastTreeTweedieTrainer TrainerEstimator test 
+        /// FastTreeTweedieTrainer TrainerEstimator test
         /// </summary>
         [Fact]
         public void TweedieRegressorEstimator()
@@ -246,7 +246,7 @@ public void TweedieRegressorEstimator()
         }
 
         /// <summary>
-        /// FastForestRegression TrainerEstimator test 
+        /// FastForestRegression TrainerEstimator test
         /// </summary>
         [Fact]
         public void FastForestRegressorEstimator()
@@ -265,7 +265,7 @@ public void FastForestRegressorEstimator()
         }
 
         /// <summary>
-        /// LightGbmMulticlass TrainerEstimator test 
+        /// LightGbmMulticlass TrainerEstimator test
         /// </summary>
         [LightGBMFact]
         public void LightGbmMulticlassEstimator()
@@ -298,7 +298,7 @@ public void LightGbmMulticlassEstimatorWithOptions()
         }
 
         /// <summary>
-        /// LightGbmMulticlass CorrectSigmoid test 
+        /// LightGbmMulticlass CorrectSigmoid test
         /// </summary>
         [LightGBMFact]
         public void LightGbmMulticlassEstimatorCorrectSigmoid()
@@ -366,7 +366,7 @@ private void LightGbmHelper(bool useSoftmax, double sigmoid, out string modelStr
             var mlContext = new MLContext(seed: 0);
             var dataView = mlContext.Data.LoadFromEnumerable(dataList);
             int numberOfTrainingIterations = 3;
-            var gbmTrainer = new LightGbmMulticlassTrainer(mlContext, 
+            var gbmTrainer = new LightGbmMulticlassTrainer(mlContext,
                 new LightGbmMulticlassTrainer.Options
                 {
                     NumberOfIterations = numberOfTrainingIterations,
@@ -683,7 +683,7 @@ private void CheckSummary(ICanGetSummaryAsIDataView modelParameters, double bias
             var quantileTrees = trees as IReadOnlyList<QuantileRegressionTree>;
             var summaryDataView = modelParameters.GetSummaryDataView(null);
             IEnumerable<SummaryDataRow> summaryDataEnumerable;
-            
+
             if (quantileTrees == null)
                 summaryDataEnumerable = ML.Data.CreateEnumerable<SummaryDataRow>(summaryDataView, true);
             else
@@ -769,7 +769,7 @@ public void FastTreeTweedieRegressorTestSummary()
             Done();
         }
 
-        [Fact]
+        [LightGBMFact]
         public void LightGbmRegressorTestSummary()
         {
             var dataView = GetRegressionPipeline();
@@ -823,7 +823,7 @@ public void FastForestBinaryClassificationTestSummary()
             Done();
         }
 
-        [Fact]
+        [LightGBMFact]
         public void LightGbmBinaryClassificationTestSummary()
         {
             var (pipeline, dataView) = GetBinaryClassificationPipeline();