1 write to Dataset
Microsoft.ML.FastTree (1)
Training\Applications\ObjectiveFunction.cs (1)
44Dataset = dataset;
45 references to Dataset
Microsoft.ML.FastTree (45)
FastTreeClassification.cs (4)
365int begin = Dataset.Boundaries[query]; 366int numDocuments = Dataset.Boundaries[query + 1] - Dataset.Boundaries[query]; 405means = _parallelTraining.GlobalMean(Dataset, tree, partitioning, Weights, false);
FastTreeRanking.cs (26)
578TrainQueriesTopLabels = new short[Dataset.NumQueries][]; 579for (int q = 0; q < Dataset.NumQueries; ++q) 582_labelCounts = new int[Dataset.NumQueries][]; 584for (int q = 0; q < Dataset.NumQueries; ++q) 592_inverseMaxDcgt = new double[Dataset.NumQueries]; 593for (int q = 0; q < Dataset.NumQueries; ++q) 598_inverseMaxDcgt = DcgCalculator.MaxDcg(_labels, Dataset.Boundaries, _maxDcgTruncationLevel, _labelCounts); 599for (int q = 0; q < Dataset.NumQueries; ++q) 603_discount = new double[Dataset.MaxDocsPerQuery]; 606_oneTwoThree = new int[Dataset.MaxDocsPerQuery]; 607for (int d = 0; d < Dataset.MaxDocsPerQuery; ++d) 618_permutationBuffers[i] = new int[Dataset.MaxDocsPerQuery]; 633_scoresCopy = new double[Dataset.NumDocs]; 634_labelsCopy = new short[Dataset.NumDocs]; 635_groupIdToTopLabel = new short[Dataset.NumDocs]; 746int begin = Dataset.Boundaries[query]; 747int numDocuments = Dataset.Boundaries[query + 1] - Dataset.Boundaries[query]; 808IgnoreNonBestDuplicates(labels, scoresToUse, permutation, Dataset.DupeIds, begin, numDocuments); 934means = _parallelTraining.GlobalMean(Dataset, tree, partitioning, Weights, _filterZeroLambdas); 954for (int d = 0; d < Dataset.MaxDocsPerQuery; ++d) 961_gainLabels = new double[Dataset.NumDocs]; 962for (int i = 0; i < Dataset.NumDocs; i++) 971int numDocuments = Dataset.Boundaries[query + 1] - Dataset.Boundaries[query]; 972int begin = Dataset.Boundaries[query];
FastTreeRegression.cs (2)
459int begin = Dataset.Boundaries[query]; 460int end = Dataset.Boundaries[query + 1];
FastTreeTweedie.cs (2)
453int begin = Dataset.Boundaries[query]; 454int end = Dataset.Boundaries[query + 1];
RandomForestClassification.cs (2)
396int begin = Dataset.Boundaries[query]; 397int end = Dataset.Boundaries[query + 1];
RandomForestRegression.cs (2)
532int begin = Dataset.Boundaries[query]; 533int end = Dataset.Boundaries[query + 1];
Training\Applications\GradientWrappers.cs (2)
51double[] sampleWeights = objFunction.Dataset.SampleWeights; 72double[] sampleWeights = objFunction.Dataset.SampleWeights;
Training\Applications\ObjectiveFunction.cs (5)
51Gradient = new double[Dataset.NumDocs]; 52Weights = new double[Dataset.NumDocs]; 63var actions = new Action[(int)Math.Ceiling((double)Dataset.NumQueries / QueryThreadChunkSize)]; 67for (int q = 0; q < Dataset.NumQueries; q += QueryThreadChunkSize) 74GetGradientChunk(start, start + Math.Min(QueryThreadChunkSize, Dataset.NumQueries - start), GradSamplingRate, sampleIndex, threadIndex);