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

602catMetaData.IsCategoricalFeature = new bool[catMetaData.NumCol]; 607for (int i = 0; i < catMetaData.NumCol; ++i) 854float[] featureValuesTemp = new float[catMetaData.NumCol]; 855for (int i = 0; i < catMetaData.NumCol; ++i) 951double[][] sampleValuePerColumn = new double[catMetaData.NumCol][]; 952int[][] sampleIndicesPerColumn = new int[catMetaData.NumCol][]; 953int[] nonZeroCntPerColumn = new int[catMetaData.NumCol]; 956for (int i = 0; i < catMetaData.NumCol; i++) 972for (int i = 0; i < catMetaData.NumCol; ++i) 1022dataset = new Dataset(sampleValuePerColumn, sampleIndicesPerColumn, catMetaData.NumCol, nonZeroCntPerColumn, sampleIdx, numRow, param, labels, weights, groups); 1034ch.Assert(dataset.GetNumCols() == catMetaData.NumCol); 1037batchSize = Math.Max(batchSize, catMetaData.NumCol); 1045int batchRow = batchSize / catMetaData.NumCol; 1051if ((long)catMetaData.NumCol * batchRow > Utils.ArrayMaxSize) 1054float[] features = new float[catMetaData.NumCol * batchRow]; 1066ch.Assert(numElem == curRowCount * catMetaData.NumCol); 1069dataset.PushRows(features, curRowCount, catMetaData.NumCol, totalRowCount - curRowCount); 1077ch.Assert(numElem == curRowCount * catMetaData.NumCol); 1080dataset.PushRows(features, curRowCount, catMetaData.NumCol, totalRowCount - curRowCount); 1086int esimateBatchRow = (int)(batchSize / (catMetaData.NumCol * density)); 1109curRowCount + 1, numElem, catMetaData.NumCol, totalRowCount - curRowCount); 1129numElem, catMetaData.NumCol, totalRowCount - curRowCount); 1138ch.Assert(features.Length >= numElem + catMetaData.NumCol); 1144for (int i = 0; i < catMetaData.NumCol; ++i) 1146numElem += catMetaData.NumCol; 1162while (lastIdx < catMetaData.NumCol) 1164numElem += catMetaData.NumCol; 1170numElem += catMetaData.NumCol; 1186for (int i = 0; i < catMetaData.NumCol; ++i)