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