TrainerEstimators\TreeEstimators.cs (33)
501[KeyType(_classNumber)]
503[VectorType(_classNumber)]
527labels[i] = (uint)featureSum % _classNumber;
528dataList.Add(new GbmExample { Features = featureVector, Label = labels[i], Score = new float[_classNumber] });
583lgbmProbabilities = new double[_rowNumber * _classNumber];
585lgbmRawScores = new double[_rowNumber * _classNumber];
633for (int j = 0; j < _classNumber; ++j)
635Assert.Equal(nativeResult0[j + i * _classNumber], mlnetPredictions[i].Score[j], 0.000001);
636if (float.IsNaN((float)nativeResult1[j + i * _classNumber]))
638sum += MathUtils.SigmoidSlow(sigmoidScale * (float)nativeResult1[j + i * _classNumber]);
640for (int j = 0; j < _classNumber; ++j)
642double prob = MathUtils.SigmoidSlow(sigmoidScale * (float)nativeResult1[j + i * _classNumber]);
669for (int j = 0; j < _classNumber; ++j)
671Assert.Equal(nativeResult0[j + i * _classNumber], mlnetPredictions[i].Score[j], 0.000001);
672if (float.IsNaN((float)nativeResult1[j + i * _classNumber]))
674sum += MathUtils.SigmoidSlow((float)sigmoidScale * (float)nativeResult1[j + i * _classNumber]);
676for (int j = 0; j < _classNumber; ++j)
678double prob = MathUtils.SigmoidSlow((float)sigmoidScale * (float)nativeResult1[j + i * _classNumber]);
704for (int j = 0; j < _classNumber; ++j)
706if (float.IsNaN((float)firstNativeResult1[j + i * _classNumber]))
708if (float.IsNaN((float)secondNativeResult1[j + i * _classNumber]))
716Assert.NotEqual((float)firstNativeResult1[j + i * _classNumber], (float)secondNativeResult1[j + i * _classNumber], 6);
740for (int j = 0; j < _classNumber; ++j)
742Assert.Equal(nativeResult0[j + i * _classNumber], mlnetPredictions[i].Score[j], 0.000001);
743sum += Math.Exp((float)nativeResult1[j + i * _classNumber]);
745for (int j = 0; j < _classNumber; ++j)
747double prob = Math.Exp(nativeResult1[j + i * _classNumber]);
769for (int j = 0; j < _classNumber; ++j)
771Assert.Equal(nativeResult0[j + i * _classNumber], mlnetPredictions[i].Score[j], 0.000001);
772sum += Math.Exp((float)nativeResult1[j + i * _classNumber]);
774for (int j = 0; j < _classNumber; ++j)
776double prob = Math.Exp(nativeResult1[j + i * _classNumber]);