576catMetaData.NumCol = catBoundaries.Count - 1; 631catMetaData.NumCol = rawNumCol;

578catMetaData.IsCategoricalFeature = new bool[catMetaData.NumCol]; 583for (int i = 0; i < catMetaData.NumCol; ++i) 827float[] featureValuesTemp = new float[catMetaData.NumCol]; 828for (int i = 0; i < catMetaData.NumCol; ++i) 924double[][] sampleValuePerColumn = new double[catMetaData.NumCol][]; 925int[][] sampleIndicesPerColumn = new int[catMetaData.NumCol][]; 926int[] nonZeroCntPerColumn = new int[catMetaData.NumCol]; 929for (int i = 0; i < catMetaData.NumCol; i++) 945for (int i = 0; i < catMetaData.NumCol; ++i) 995dataset = new Dataset(sampleValuePerColumn, sampleIndicesPerColumn, catMetaData.NumCol, nonZeroCntPerColumn, sampleIdx, numRow, param, labels, weights, groups); 1007ch.Assert(dataset.GetNumCols() == catMetaData.NumCol); 1010batchSize = Math.Max(batchSize, catMetaData.NumCol); 1018int batchRow = batchSize / catMetaData.NumCol; 1024if ((long)catMetaData.NumCol * batchRow > Utils.ArrayMaxSize) 1027float[] features = new float[catMetaData.NumCol * batchRow]; 1039ch.Assert(numElem == curRowCount * catMetaData.NumCol); 1042dataset.PushRows(features, curRowCount, catMetaData.NumCol, totalRowCount - curRowCount); 1050ch.Assert(numElem == curRowCount * catMetaData.NumCol); 1053dataset.PushRows(features, curRowCount, catMetaData.NumCol, totalRowCount - curRowCount); 1059int esimateBatchRow = (int)(batchSize / (catMetaData.NumCol * density)); 1082curRowCount + 1, numElem, catMetaData.NumCol, totalRowCount - curRowCount); 1102numElem, catMetaData.NumCol, totalRowCount - curRowCount); 1111ch.Assert(features.Length >= numElem + catMetaData.NumCol); 1117for (int i = 0; i < catMetaData.NumCol; ++i) 1119numElem += catMetaData.NumCol; 1135while (lastIdx < catMetaData.NumCol) 1137numElem += catMetaData.NumCol; 1143numElem += catMetaData.NumCol; 1159for (int i = 0; i < catMetaData.NumCol; ++i)