4 instantiations of FastForestRegressionTrainer
Microsoft.ML.FastTree (4)
RandomForestRegression.cs (1)
603() => new FastForestRegressionTrainer(host, input),
TreeEnsembleFeaturizationEstimator.cs (1)
373var trainer = new FastForestRegressionTrainer(Env, _trainerOptions);
TreeTrainersCatalog.cs (2)
363return new FastForestRegressionTrainer(env, labelColumnName, featureColumnName, exampleWeightColumnName, numberOfLeaves, numberOfTrees, minimumExampleCountPerLeaf); 385return new FastForestRegressionTrainer(env, options);
55 references to FastForestRegressionTrainer
Microsoft.ML.AutoML (7)
API\RegressionExperiment.cs (1)
81/// See <see cref="FastForestRegressionTrainer"/>.
SweepableEstimator\Estimators\FastForest.cs (1)
31var option = new FastForestRegressionTrainer.Options()
Sweepers\SmacSweeper.cs (2)
129var trainer = _context.Regression.Trainers.FastForest(new FastForestRegressionTrainer.Options()
TrainerExtensions\RegressionTrainerExtensions.cs (1)
25var options = TrainerExtensionUtil.CreateOptions<FastForestRegressionTrainer.Options>(sweepParams, columnInfo.LabelColumnName);
Tuner\SmacTuner.cs (2)
141var trainer = _context.Regression.Trainers.FastForest(new FastForestRegressionTrainer.Options()
Microsoft.ML.FastTree (29)
FastTreeRegression.cs (1)
473/// Model parameters for <see cref="FastForestRegressionTrainer"/>.
RandomForestRegression.cs (18)
20[assembly: LoadableClass(FastForestRegressionTrainer.Summary, typeof(FastForestRegressionTrainer), typeof(FastForestRegressionTrainer.Options), 22FastForestRegressionTrainer.UserNameValue, 23FastForestRegressionTrainer.LoadNameValue, 24FastForestRegressionTrainer.ShortName)] 33/// Model parameters for <see cref="FastForestRegressionTrainer"/>. 291/// <seealso cref="TreeExtensions.FastForest(RegressionCatalog.RegressionTrainers, FastForestRegressionTrainer.Options)"/> 294: RandomForestTrainerBase<FastForestRegressionTrainer.Options, RegressionPredictionTransformer<FastForestRegressionModelParameters>, FastForestRegressionModelParameters> 297/// Options for the <see cref="FastForestRegressionTrainer"/> as used in 318/// Initializes a new instance of <see cref="FastForestRegressionTrainer"/> 341/// Initializes a new instance of <see cref="FastForestRegressionTrainer"/> by using the <see cref="Options"/> class. 498/// Trains a <see cref="FastForestRegressionTrainer"/> using both training and validation data, returns 592Desc = FastForestRegressionTrainer.Summary, 593UserName = FastForestRegressionTrainer.LoadNameValue, 594ShortName = FastForestRegressionTrainer.ShortName)] 595public static CommonOutputs.RegressionOutput TrainRegression(IHostEnvironment env, FastForestRegressionTrainer.Options input) 602return TrainerEntryPointsUtils.Train<FastForestRegressionTrainer.Options, CommonOutputs.RegressionOutput>(host, input,
TreeEnsembleFeaturizationEstimator.cs (4)
352private readonly FastForestRegressionTrainer.Options _trainerOptions; 360/// The configuration of <see cref="FastForestRegressionTrainer"/> used to train the underlying <see cref="TreeEnsembleModelParameters"/>. 362public FastForestRegressionTrainer.Options TrainerOptions; 373var trainer = new FastForestRegressionTrainer(Env, _trainerOptions);
TreeTrainersCatalog.cs (6)
337/// Create <see cref="FastForestRegressionTrainer"/>, which predicts a target using a decision tree regression model. 353public static FastForestRegressionTrainer FastForest(this RegressionCatalog.RegressionTrainers catalog, 367/// Create <see cref="FastForestRegressionTrainer"/> with advanced options, which predicts a target using a decision tree regression model. 378public static FastForestRegressionTrainer FastForest(this RegressionCatalog.RegressionTrainers catalog, 379FastForestRegressionTrainer.Options options) 462/// Create <see cref="FastForestRegressionFeaturizationEstimator"/>, which uses <see cref="FastForestRegressionTrainer"/> to train <see cref="TreeEnsembleModelParameters"/> to create tree-based features.
Microsoft.ML.IntegrationTests (2)
Evaluation.cs (1)
271.Append(mlContext.Regression.Trainers.FastForest(new FastForestRegressionTrainer.Options { NumberOfThreads = 1 }));
IntrospectiveTraining.cs (1)
40new FastForestRegressionTrainer.Options { NumberOfLeaves = 5, NumberOfTrees = 3, NumberOfThreads = 1 }));
Microsoft.ML.Samples (4)
Dynamic\Trainers\Regression\FastForest.cs (1)
30var pipeline = mlContext.Regression.Trainers.FastForest(
Dynamic\Trainers\Regression\FastForestWithOptions.cs (2)
31var options = new FastForestRegressionTrainer.Options 44var pipeline =
Dynamic\Transforms\TreeFeaturization\FastForestRegressionFeaturizationWithOptions.cs (1)
46var trainerOptions = new FastForestRegressionTrainer.Options
Microsoft.ML.Samples.OneDal (3)
Program.cs (3)
103FastForestRegressionTrainer.Options options = new FastForestRegressionTrainer.Options(); 111var trainer = mlContext.Regression.Trainers.FastForest(options);
Microsoft.ML.Sweeper (2)
Algorithms\SmacSweeper.cs (2)
136var trainer = new FastForestRegressionTrainer(_host, 137new FastForestRegressionTrainer.Options
Microsoft.ML.Tests (8)
TrainerEstimators\TreeEnsembleFeaturizerTest.cs (4)
473var trainerOptions = new FastForestRegressionTrainer.Options 587var trainerOptions = new FastForestRegressionTrainer.Options 642var trainerOptions = new FastForestRegressionTrainer.Options 774var trainerOptions = new FastForestRegressionTrainer.Options
TrainerEstimators\TreeEstimators.cs (4)
290var trainer = ML.Regression.Trainers.FastForest( 291new FastForestRegressionTrainer.Options 927var trainer = ML.Regression.Trainers.FastForest( 928new FastForestRegressionTrainer.Options { NumberOfTrees = 10, NumberOfThreads = 1, NumberOfLeaves = 5 });