TrainerEstimators\TreeEstimators.cs (33)
430[KeyType(_classNumber)]
432[VectorType(_classNumber)]
456labels[i] = (uint)featureSum % _classNumber;
457dataList.Add(new GbmExample { Features = featureVector, Label = labels[i], Score = new float[_classNumber] });
512lgbmProbabilities = new double[_rowNumber * _classNumber];
514lgbmRawScores = new double[_rowNumber * _classNumber];
562for (int j = 0; j < _classNumber; ++j)
564Assert.Equal(nativeResult0[j + i * _classNumber], mlnetPredictions[i].Score[j], 0.000001);
565if (float.IsNaN((float)nativeResult1[j + i * _classNumber]))
567sum += MathUtils.SigmoidSlow(sigmoidScale * (float)nativeResult1[j + i * _classNumber]);
569for (int j = 0; j < _classNumber; ++j)
571double prob = MathUtils.SigmoidSlow(sigmoidScale * (float)nativeResult1[j + i * _classNumber]);
598for (int j = 0; j < _classNumber; ++j)
600Assert.Equal(nativeResult0[j + i * _classNumber], mlnetPredictions[i].Score[j], 0.000001);
601if (float.IsNaN((float)nativeResult1[j + i * _classNumber]))
603sum += MathUtils.SigmoidSlow((float)sigmoidScale * (float)nativeResult1[j + i * _classNumber]);
605for (int j = 0; j < _classNumber; ++j)
607double prob = MathUtils.SigmoidSlow((float)sigmoidScale * (float)nativeResult1[j + i * _classNumber]);
633for (int j = 0; j < _classNumber; ++j)
635if (float.IsNaN((float)firstNativeResult1[j + i * _classNumber]))
637if (float.IsNaN((float)secondNativeResult1[j + i * _classNumber]))
645Assert.NotEqual((float)firstNativeResult1[j + i * _classNumber], (float)secondNativeResult1[j + i * _classNumber], 6);
669for (int j = 0; j < _classNumber; ++j)
671Assert.Equal(nativeResult0[j + i * _classNumber], mlnetPredictions[i].Score[j], 0.000001);
672sum += Math.Exp((float)nativeResult1[j + i * _classNumber]);
674for (int j = 0; j < _classNumber; ++j)
676double prob = Math.Exp(nativeResult1[j + i * _classNumber]);
698for (int j = 0; j < _classNumber; ++j)
700Assert.Equal(nativeResult0[j + i * _classNumber], mlnetPredictions[i].Score[j], 0.000001);
701sum += Math.Exp((float)nativeResult1[j + i * _classNumber]);
703for (int j = 0; j < _classNumber; ++j)
705double prob = Math.Exp(nativeResult1[j + i * _classNumber]);