1 instantiation of GbmExample
Microsoft.ML.Tests (1)
TrainerEstimators\TreeEstimators.cs (1)
457dataList.Add(new GbmExample { Features = featureVector, Label = labels[i], Score = new float[_classNumber] });
9 references to GbmExample
Microsoft.ML.Tests (9)
TrainerEstimators\TreeEstimators.cs (9)
436private void LightGbmHelper(bool useSoftmax, double sigmoid, out string modelString, out List<GbmExample> mlnetPredictions, out double[] lgbmRawScores, out double[] lgbmProbabilities, bool unbalancedSets = false) 444var dataList = new List<GbmExample>(); 476mlnetPredictions = mlContext.Data.CreateEnumerable<GbmExample>(predicted, false).ToList(); 552LightGbmHelper(useSoftmax: false, sigmoid: sigmoidScale, out string modelString, out List<GbmExample> mlnetPredictions, out double[] nativeResult1, out double[] nativeResult0); 587LightGbmHelper(useSoftmax: false, sigmoid: sigmoidScale, out string modelString, out List<GbmExample> mlnetPredictions, out double[] nativeResult1, out double[] nativeResult0); 626LightGbmHelper(useSoftmax: false, sigmoid: firstSigmoidScale, out string firstModelString, out List<GbmExample> firstMlnetPredictions, out double[] firstNativeResult1, out double[] firstNativeResult0); 627LightGbmHelper(useSoftmax: false, sigmoid: secondSigmoidScale, out string secondModelString, out List<GbmExample> secondMlnetPredictions, out double[] secondNativeResult1, out double[] secondNativeResult0); 659LightGbmHelper(useSoftmax: true, sigmoid: .5, out string modelString, out List<GbmExample> mlnetPredictions, out double[] nativeResult1, out double[] nativeResult0); 688LightGbmHelper(useSoftmax: true, sigmoid: .5, out string modelString, out List<GbmExample> mlnetPredictions, out double[] nativeResult1, out double[] nativeResult0, unbalancedSets: true);