TrainerEstimators\TreeEstimators.cs (15)
499[VectorType(_columnNumber)]
511var dataMatrix = new float[_rowNumber * _columnNumber];
519var featureVector = new float[_columnNumber];
520for (/*column index*/ int j = 0; j < _columnNumber; ++j)
522int featureValue = (j + i * _columnNumber) % 10;
524dataMatrix[j + i * _columnNumber] = featureValue;
552double[][] sampleValueGroupedByColumn = new double[_columnNumber][];
553int[][] sampleIndicesGroupedByColumn = new int[_columnNumber][];
554int[] sampleNonZeroCntPerColumn = new int[_columnNumber];
555for (int j = 0; j < _columnNumber; ++j)
565sampleValueGroupedByColumn[j][i] = dataMatrix[j + i * _columnNumber];
577var gbmDataSet = new Trainers.LightGbm.Dataset(sampleValueGroupedByColumn, sampleIndicesGroupedByColumn, _columnNumber, sampleNonZeroCntPerColumn, _rowNumber, _rowNumber, "", floatLabels);
580gbmDataSet.PushRows(dataMatrix, _rowNumber, _columnNumber, 0);
607_rowNumber, _columnNumber, 1, (int)WrappedLightGbmInterface.CApiPredictType.Normal, 0, numberOfTrainingIterations, "", ref nativeLength, result0);
609_rowNumber, _columnNumber, 1, (int)WrappedLightGbmInterface.CApiPredictType.Raw, 0, numberOfTrainingIterations, "", ref nativeLength, result1);