600catMetaData.NumCol = catBoundaries.Count - 1; 655catMetaData.NumCol = rawNumCol;

602catMetaData.IsCategoricalFeature = new bool[catMetaData.NumCol]; 607for (int i = 0; i < catMetaData.NumCol; ++i) 851float[] featureValuesTemp = new float[catMetaData.NumCol]; 852for (int i = 0; i < catMetaData.NumCol; ++i) 948double[][] sampleValuePerColumn = new double[catMetaData.NumCol][]; 949int[][] sampleIndicesPerColumn = new int[catMetaData.NumCol][]; 950int[] nonZeroCntPerColumn = new int[catMetaData.NumCol]; 953for (int i = 0; i < catMetaData.NumCol; i++) 969for (int i = 0; i < catMetaData.NumCol; ++i) 1019dataset = new Dataset(sampleValuePerColumn, sampleIndicesPerColumn, catMetaData.NumCol, nonZeroCntPerColumn, sampleIdx, numRow, param, labels, weights, groups); 1031ch.Assert(dataset.GetNumCols() == catMetaData.NumCol); 1034batchSize = Math.Max(batchSize, catMetaData.NumCol); 1042int batchRow = batchSize / catMetaData.NumCol; 1048if ((long)catMetaData.NumCol * batchRow > Utils.ArrayMaxSize) 1051float[] features = new float[catMetaData.NumCol * batchRow]; 1063ch.Assert(numElem == curRowCount * catMetaData.NumCol); 1066dataset.PushRows(features, curRowCount, catMetaData.NumCol, totalRowCount - curRowCount); 1074ch.Assert(numElem == curRowCount * catMetaData.NumCol); 1077dataset.PushRows(features, curRowCount, catMetaData.NumCol, totalRowCount - curRowCount); 1083int esimateBatchRow = (int)(batchSize / (catMetaData.NumCol * density)); 1106curRowCount + 1, numElem, catMetaData.NumCol, totalRowCount - curRowCount); 1126numElem, catMetaData.NumCol, totalRowCount - curRowCount); 1135ch.Assert(features.Length >= numElem + catMetaData.NumCol); 1141for (int i = 0; i < catMetaData.NumCol; ++i) 1143numElem += catMetaData.NumCol; 1159while (lastIdx < catMetaData.NumCol) 1161numElem += catMetaData.NumCol; 1167numElem += catMetaData.NumCol; 1183for (int i = 0; i < catMetaData.NumCol; ++i)