2 writes to GamTrainerOptions
Microsoft.ML.FastTree (2)
GamTrainer.cs (2)
178GamTrainerOptions = new TOptions(); 211GamTrainerOptions = options;
32 references to GamTrainerOptions
Microsoft.ML.FastTree (32)
GamClassification.cs (6)
151GamTrainerOptions.LearningRate, 154GamTrainerOptions.UnbalancedSets, 155GamTrainerOptions.MaximumTreeOutput, 156GamTrainerOptions.GetDerivativesSampleRate, 158GamTrainerOptions.Seed, 168PruningLossIndex = GamTrainerOptions.UnbalancedSets ? 3 /*Unbalanced sets loss*/ : 1 /*normal loss*/;
GamRegression.cs (2)
114return new FastTreeRegressionTrainer.ObjectiveImpl(TrainSet, GamTrainerOptions); 119var validTest = new RegressionTest(ValidSetScore, GamTrainerOptions.PruningMetrics);
GamTrainer.cs (24)
179GamTrainerOptions.NumberOfIterations = numberOfIterations; 180GamTrainerOptions.LearningRate = learningRate; 181GamTrainerOptions.MaximumBinCountPerFeature = maximumBinCountPerFeature; 183GamTrainerOptions.LabelColumnName = label.Name; 184GamTrainerOptions.FeatureColumnName = featureColumnName; 187GamTrainerOptions.ExampleWeightColumnName = weightCrowGroupColumnName; 190_gainConfidenceInSquaredStandardDeviations = Math.Pow(ProbabilityFunctions.Probit(1 - (1 - GamTrainerOptions.GainConfidenceLevel) * 0.5), 2); 191_entropyCoefficient = GamTrainerOptions.EntropyCoefficient * 1e-6; 214_gainConfidenceInSquaredStandardDeviations = Math.Pow(ProbabilityFunctions.Probit(1 - (1 - GamTrainerOptions.GainConfidenceLevel) * 0.5), 2); 215_entropyCoefficient = GamTrainerOptions.EntropyCoefficient * 1e-6; 256var useTranspose = UseTranspose(GamTrainerOptions.DiskTranspose, trainData); 257var instanceConverter = new ExamplesToFastTreeBins(Host, GamTrainerOptions.MaximumBinCountPerFeature, useTranspose, !GamTrainerOptions.FeatureFlocks, GamTrainerOptions.MinimumExampleCountPerLeaf, float.PositiveInfinity); 297int iterations = GamTrainerOptions.NumberOfIterations; 363globalFeatureIndex, flockIndex, subFeatureIndex, GamTrainerOptions.MinimumExampleCountPerLeaf, HasWeights, 426int bestIteration = GamTrainerOptions.NumberOfIterations; 427if (GamTrainerOptions.EnablePruning && PruningTest != null) 438if (bestIteration != GamTrainerOptions.NumberOfIterations) 439ch.Info($"Best Iteration ({lossFunctionName}): {bestIteration} @ {bestLoss:G6} (vs {GamTrainerOptions.NumberOfIterations} @ {finalResult.FinalValue:G6})."); 579_subGraph.Splits[globalFeatureIndex][iteration].LteValue = GamTrainerOptions.LearningRate * splitinfo.LteOutput; 580_subGraph.Splits[globalFeatureIndex][iteration].GtValue = GamTrainerOptions.LearningRate * splitinfo.GTOutput; 595_subGraph = new SubGraph(TrainSet.NumFeatures, GamTrainerOptions.NumberOfIterations); 604ThreadTaskManager.Initialize(GamTrainerOptions.NumberOfThreads ?? Environment.ProcessorCount);