1 implementation of IParallelTraining
Microsoft.ML.FastTree (1)
Training\Parallel\SingleTrainer.cs (1)
22internal sealed class SingleTrainer : IParallelTraining
32 references to IParallelTraining
Microsoft.ML.FastTree (32)
FastTree.cs (7)
62private protected IParallelTraining ParallelTraining; 957IParallelTraining parallelTraining, int[] categoricalFeatureIndices, bool categoricalSplit) 1267IParallelTraining parallelTraining, int[] categoricalFeatureIndices, bool categoricalSplit) 1325private Dataset Construct(RoleMappedData examples, ref int numExamples, int maxBins, IParallelTraining parallelTraining) 1782PredictionKind kind, IParallelTraining parallelTraining, int[] categoricalFeatureIndices, bool categoricalSplit) 1902private void InitializeBins(int maxBins, IParallelTraining parallelTraining) 2744public Dataset FindBinsAndReturnDataset(RoleMappedData data, PredictionKind kind, IParallelTraining parallelTraining,
FastTreeClassification.cs (2)
328private readonly IParallelTraining _parallelTraining; 342IParallelTraining parallelTraining)
FastTreeRanking.cs (2)
561private readonly IParallelTraining _parallelTraining; 567public LambdaRankObjectiveFunction(Dataset trainset, short[] labels, Options options, IParallelTraining parallelTraining)
GamTrainer.cs (1)
166private protected IParallelTraining ParallelTraining;
Training\Parallel\IParallelTraining.cs (1)
152internal interface ISupportParallelTraining : IComponentFactory<IParallelTraining>
Training\Parallel\SingleTrainer.cs (16)
24void IParallelTraining.CacheHistogram(bool isSmallerLeaf, int featureIdx, int subfeature, SufficientStatsBase sufficientStatsBase, bool hasWeights) 28bool IParallelTraining.IsNeedFindLocalBestSplit() 33void IParallelTraining.FindGlobalBestSplit(LeafSplitCandidates smallerChildSplitCandidates, 40void IParallelTraining.GetGlobalDataCountInLeaf(int leafIdx, ref int cnt) 44bool[] IParallelTraining.GetLocalBinConstructionFeatures(int numFeatures) 49double[] IParallelTraining.GlobalMean(Dataset dataset, InternalRegressionTree tree, DocumentPartitioning partitioning, double[] weights, bool filterZeroLambdas) 59void IParallelTraining.PerformGlobalSplit(int leaf, int lteChild, int gtChild, SplitInfo splitInfo) 63void IParallelTraining.InitIteration(ref bool[] activeFeatures) 67void IParallelTraining.InitEnvironment() 71void IParallelTraining.InitTreeLearner(Dataset trainData, int maxNumLeaves, int maxCatSplitPoints, ref int minDocInLeaf) 75void IParallelTraining.SyncGlobalBoundary(int numFeatures, int maxBin, Double[][] binUpperBounds) 79void IParallelTraining.FinalizeEnvironment() 83void IParallelTraining.FinalizeTreeLearner() 87void IParallelTraining.FinalizeIteration() 91bool IParallelTraining.IsSkipNonSplittableHistogram() 100public IParallelTraining CreateComponent(IHostEnvironment env) => new SingleTrainer();
Training\TreeLearners\FastForestLeastSquaresTreeLearner.cs (1)
17Double gainConfidenceLevel, int maxCategoricalGroupsPerNode, int maxCategoricalSplitPointsPerNode, bool quantileEnabled, int quantileSampleCount, IParallelTraining parallelTraining,
Training\TreeLearners\LeastSquaresRegressionTreeLearner.cs (2)
77private readonly IParallelTraining _parallelTraining; 124double bsrMaxTreeOutput, IParallelTraining parallelTraining, double minDocsPercentageForCategoricalSplit,