260TrainSet = instanceConverter.FindBinsAndReturnDataset(trainData, PredictionKind, ParallelTraining, null, false);

149TrainSet, 150ConvertTargetsToBool(TrainSet.Targets),

114return new FastTreeRegressionTrainer.ObjectiveImpl(TrainSet, GamTrainerOptions);

152private bool HasWeights => TrainSet?.SampleWeights != null; 241TrainSetScore = new ScoreTracker("train", TrainSet, null); 264Host.Assert(FeatureMap == null || FeatureMap.Length == TrainSet.NumFeatures); 304var sumWeights = HasWeights ? TrainSet.SampleWeights.Sum() : 0; 331TrainSet.FlockToFirstFeature(flockIndex), 333TrainSet.NumDocs, 337TrainSet.SampleWeights, 339}, TrainSet.NumFlocks); 350}, TrainSet.NumFeatures); 358TrainSet.MapFeatureToFlockAndSubFeature(globalFeatureIndex, out flockIndex, out subFeatureIndex); 365TrainSet.Flocks[flockIndex].Trust(subFeatureIndex), 0); 378UpdateScoresForSet(TrainSet, TrainSetScore.Scores, iteration); 445BinEffects = new double[TrainSet.NumFeatures][]; 446for (int featureIndex = 0; featureIndex < TrainSet.NumFeatures; featureIndex++) 448TrainSet.MapFeatureToFlockAndSubFeature(featureIndex, out int flockIndex, out int subFeatureIndex); 449int numOfBins = TrainSet.Flocks[flockIndex].BinCount(subFeatureIndex); 494DefineDocumentThreadBlocks(TrainSet.NumDocs, BlockingThreadPool.NumThreads, out int[] trainThreadBlocks); 505var featureIndexer = TrainSet.GetIndexer(featureIndex); 529meanEffects[featureIndex] /= TrainSet.NumDocs; 544BinUpperBounds = new double[TrainSet.NumFeatures][]; 548for (int i = 0; i < TrainSet.NumFeatures; i++) 550TrainSet.MapFeatureToFlockAndSubFeature(i, out int flockIndex, out int subFeatureIndex); 551double[] binUpperBound = TrainSet.Flocks[flockIndex].BinUpperBounds(subFeatureIndex); 585_histogram = new SufficientStatsBase[TrainSet.Flocks.Length]; 586for (int i = 0; i < TrainSet.Flocks.Length; i++) 587_histogram[i] = TrainSet.Flocks[i].CreateSufficientStats(HasWeights); 595_subGraph = new SubGraph(TrainSet.NumFeatures, GamTrainerOptions.NumberOfIterations); 596_leafSplitCandidates = new LeastSquaresRegressionTreeLearner.LeafSplitCandidates(TrainSet);