TrainerEstimators\TreeEstimators.cs (33)
432[KeyType(_classNumber)]
434[VectorType(_classNumber)]
458labels[i] = (uint)featureSum % _classNumber;
459dataList.Add(new GbmExample { Features = featureVector, Label = labels[i], Score = new float[_classNumber] });
514lgbmProbabilities = new double[_rowNumber * _classNumber];
516lgbmRawScores = new double[_rowNumber * _classNumber];
564for (int j = 0; j < _classNumber; ++j)
566Assert.Equal(nativeResult0[j + i * _classNumber], mlnetPredictions[i].Score[j], 0.000001);
567if (float.IsNaN((float)nativeResult1[j + i * _classNumber]))
569sum += MathUtils.SigmoidSlow(sigmoidScale * (float)nativeResult1[j + i * _classNumber]);
571for (int j = 0; j < _classNumber; ++j)
573double prob = MathUtils.SigmoidSlow(sigmoidScale * (float)nativeResult1[j + i * _classNumber]);
600for (int j = 0; j < _classNumber; ++j)
602Assert.Equal(nativeResult0[j + i * _classNumber], mlnetPredictions[i].Score[j], 0.000001);
603if (float.IsNaN((float)nativeResult1[j + i * _classNumber]))
605sum += MathUtils.SigmoidSlow((float)sigmoidScale * (float)nativeResult1[j + i * _classNumber]);
607for (int j = 0; j < _classNumber; ++j)
609double prob = MathUtils.SigmoidSlow((float)sigmoidScale * (float)nativeResult1[j + i * _classNumber]);
635for (int j = 0; j < _classNumber; ++j)
637if (float.IsNaN((float)firstNativeResult1[j + i * _classNumber]))
639if (float.IsNaN((float)secondNativeResult1[j + i * _classNumber]))
647Assert.NotEqual((float)firstNativeResult1[j + i * _classNumber], (float)secondNativeResult1[j + i * _classNumber], 6);
671for (int j = 0; j < _classNumber; ++j)
673Assert.Equal(nativeResult0[j + i * _classNumber], mlnetPredictions[i].Score[j], 0.000001);
674sum += Math.Exp((float)nativeResult1[j + i * _classNumber]);
676for (int j = 0; j < _classNumber; ++j)
678double prob = Math.Exp(nativeResult1[j + i * _classNumber]);
700for (int j = 0; j < _classNumber; ++j)
702Assert.Equal(nativeResult0[j + i * _classNumber], mlnetPredictions[i].Score[j], 0.000001);
703sum += Math.Exp((float)nativeResult1[j + i * _classNumber]);
705for (int j = 0; j < _classNumber; ++j)
707double prob = Math.Exp(nativeResult1[j + i * _classNumber]);