TrainerEstimators\TreeEstimators.cs (15)
430[VectorType(_columnNumber)]
442var dataMatrix = new float[_rowNumber * _columnNumber];
450var featureVector = new float[_columnNumber];
451for (/*column index*/ int j = 0; j < _columnNumber; ++j)
453int featureValue = (j + i * _columnNumber) % 10;
455dataMatrix[j + i * _columnNumber] = featureValue;
483double[][] sampleValueGroupedByColumn = new double[_columnNumber][];
484int[][] sampleIndicesGroupedByColumn = new int[_columnNumber][];
485int[] sampleNonZeroCntPerColumn = new int[_columnNumber];
486for (int j = 0; j < _columnNumber; ++j)
496sampleValueGroupedByColumn[j][i] = dataMatrix[j + i * _columnNumber];
508var gbmDataSet = new Trainers.LightGbm.Dataset(sampleValueGroupedByColumn, sampleIndicesGroupedByColumn, _columnNumber, sampleNonZeroCntPerColumn, _rowNumber, _rowNumber, "", floatLabels);
511gbmDataSet.PushRows(dataMatrix, _rowNumber, _columnNumber, 0);
538_rowNumber, _columnNumber, 1, (int)WrappedLightGbmInterface.CApiPredictType.Normal, 0, numberOfTrainingIterations, "", ref nativeLength, result0);
540_rowNumber, _columnNumber, 1, (int)WrappedLightGbmInterface.CApiPredictType.Raw, 0, numberOfTrainingIterations, "", ref nativeLength, result1);