5 instantiations of FastTreeRegressionTrainer
Microsoft.ML.FastTree (5)
FastTreeArguments.cs (1)
151
ITrainer IComponentFactory<ITrainer>.CreateComponent(IHostEnvironment env) => new
FastTreeRegressionTrainer
(env, this);
FastTreeRegression.cs (1)
542
() => new
FastTreeRegressionTrainer
(host, input),
TreeEnsembleFeaturizationEstimator.cs (1)
287
var trainer = new
FastTreeRegressionTrainer
(Env, _trainerOptions);
TreeTrainersCatalog.cs (2)
47
return new
FastTreeRegressionTrainer
(env, labelColumnName, featureColumnName, exampleWeightColumnName, numberOfLeaves, numberOfTrees, minimumExampleCountPerLeaf, learningRate);
69
return new
FastTreeRegressionTrainer
(env, options);
48 references to FastTreeRegressionTrainer
Microsoft.ML.AutoML (3)
API\RegressionExperiment.cs (1)
86
/// See <see cref="
FastTreeRegressionTrainer
"/>.
SweepableEstimator\Estimators\FastTree.cs (1)
36
var option = new
FastTreeRegressionTrainer
.Options()
TrainerExtensions\RegressionTrainerExtensions.cs (1)
47
var options = TrainerExtensionUtil.CreateOptions<
FastTreeRegressionTrainer
.Options>(sweepParams, columnInfo.LabelColumnName);
Microsoft.ML.FastTree (32)
FastTreeArguments.cs (2)
14
[assembly: EntryPointModule(typeof(
FastTreeRegressionTrainer
.Options))]
115
/// Options for the <see cref="
FastTreeRegressionTrainer
"/> as used in
FastTreeRanking.cs (1)
65
/// <seealso cref="TreeExtensions.FastTree(RegressionCatalog.RegressionTrainers,
FastTreeRegressionTrainer
.Options)"/>
FastTreeRegression.cs (16)
14
[assembly: LoadableClass(
FastTreeRegressionTrainer
.Summary, typeof(
FastTreeRegressionTrainer
), typeof(
FastTreeRegressionTrainer
.Options),
16
FastTreeRegressionTrainer
.UserNameValue,
17
FastTreeRegressionTrainer
.LoadNameValue,
18
FastTreeRegressionTrainer
.ShortName,
56
/// <seealso cref="TreeExtensions.FastTree(RegressionCatalog.RegressionTrainers,
FastTreeRegressionTrainer
.Options)"/>
59
: BoostingFastTreeTrainerBase<
FastTreeRegressionTrainer
.Options, RegressionPredictionTransformer<FastTreeRegressionModelParameters>, FastTreeRegressionModelParameters>
76
/// Initializes a new instance of <see cref="
FastTreeRegressionTrainer
"/>
99
/// Initializes a new instance of <see cref="
FastTreeRegressionTrainer
"/> by using the <see cref="Options"/> class.
195
/// Trains a <see cref="
FastTreeRegressionTrainer
"/> using both training and validation data, returns
531
Desc =
FastTreeRegressionTrainer
.Summary,
532
UserName =
FastTreeRegressionTrainer
.UserNameValue,
533
ShortName =
FastTreeRegressionTrainer
.ShortName)]
534
public static CommonOutputs.RegressionOutput TrainRegression(IHostEnvironment env,
FastTreeRegressionTrainer
.Options input)
541
return TrainerEntryPointsUtils.Train<
FastTreeRegressionTrainer
.Options, CommonOutputs.RegressionOutput>(host, input,
GamRegression.cs (1)
114
return new
FastTreeRegressionTrainer
.ObjectiveImpl(TrainSet, GamTrainerOptions);
RandomForestRegression.cs (1)
526
_labels =
FastTreeRegressionTrainer
.GetDatasetRegressionLabels(trainData);
Training\Test.cs (1)
527
_labels =
FastTreeRegressionTrainer
.GetDatasetRegressionLabels(scoreTracker.Dataset);
TreeEnsembleFeaturizationEstimator.cs (4)
266
private readonly
FastTreeRegressionTrainer
.Options _trainerOptions;
274
/// The configuration of <see cref="
FastTreeRegressionTrainer
"/> used to train the underlying <see cref="TreeEnsembleModelParameters"/>.
276
public
FastTreeRegressionTrainer
.Options TrainerOptions;
287
var
trainer = new FastTreeRegressionTrainer(Env, _trainerOptions);
TreeTrainersCatalog.cs (6)
19
/// Create <see cref="
FastTreeRegressionTrainer
"/>, which predicts a target using a decision tree regression model.
36
public static
FastTreeRegressionTrainer
FastTree(this RegressionCatalog.RegressionTrainers catalog,
51
/// Create <see cref="
FastTreeRegressionTrainer
"/> with advanced options, which predicts a target using a decision tree regression model.
62
public static
FastTreeRegressionTrainer
FastTree(this RegressionCatalog.RegressionTrainers catalog,
63
FastTreeRegressionTrainer
.Options options)
483
/// Create <see cref="FastTreeRegressionFeaturizationEstimator"/>, which uses <see cref="
FastTreeRegressionTrainer
"/> to train <see cref="TreeEnsembleModelParameters"/> to create tree-based features.
Microsoft.ML.IntegrationTests (4)
ModelFiles.cs (2)
50
new
FastTreeRegressionTrainer
.Options { NumberOfThreads = 1, NumberOfTrees = 10 }));
97
new
FastTreeRegressionTrainer
.Options { NumberOfThreads = 1, NumberOfTrees = 10 }));
ONNX.cs (1)
44
new
FastTreeRegressionTrainer
.Options { NumberOfThreads = 1, NumberOfTrees = 10 }));
Validation.cs (1)
121
var trainedModel = mlContext.Regression.Trainers.FastTree(new
FastTreeRegressionTrainer
.Options
Microsoft.ML.Samples (4)
Dynamic\Trainers\Regression\FastTree.cs (1)
30
var
pipeline = mlContext.Regression.Trainers.FastTree(
Dynamic\Trainers\Regression\FastTreeWithOptions.cs (2)
31
var options = new
FastTreeRegressionTrainer
.Options
47
var
pipeline =
Dynamic\Transforms\TreeFeaturization\FastTreeRegressionFeaturizationWithOptions.cs (1)
46
var trainerOptions = new
FastTreeRegressionTrainer
.Options
Microsoft.ML.Tests (5)
TrainerEstimators\TreeEnsembleFeaturizerTest.cs (1)
435
var trainerOptions = new
FastTreeRegressionTrainer
.Options
TrainerEstimators\TreeEstimators.cs (4)
216
var
trainer = ML.Regression.Trainers.FastTree(
217
new
FastTreeRegressionTrainer
.Options { NumberOfTrees = 10, NumberOfThreads = 1, NumberOfLeaves = 5 });
909
var
trainer = ML.Regression.Trainers.FastTree(
910
new
FastTreeRegressionTrainer
.Options { NumberOfTrees = 10, NumberOfThreads = 1, NumberOfLeaves = 5 });