5 instantiations of FastTreeRankingTrainer
Microsoft.ML.FastTree (5)
FastTreeArguments.cs (1)
308
ITrainer IComponentFactory<ITrainer>.CreateComponent(IHostEnvironment env) => new
FastTreeRankingTrainer
(env, this);
FastTreeRanking.cs (1)
1091
() => new
FastTreeRankingTrainer
(host, input),
TreeEnsembleFeaturizationEstimator.cs (1)
416
var trainer = new
FastTreeRankingTrainer
(Env, _trainerOptions);
TreeTrainersCatalog.cs (2)
157
return new
FastTreeRankingTrainer
(env, labelColumnName, featureColumnName, rowGroupColumnName, exampleWeightColumnName, numberOfLeaves, numberOfTrees, minimumExampleCountPerLeaf, learningRate);
179
return new
FastTreeRankingTrainer
(env, options);
46 references to FastTreeRankingTrainer
Microsoft.ML.AutoML (3)
API\RankingExperiment.cs (1)
69
/// See <see cref="
FastTreeRankingTrainer
"/>.
TrainerExtensions\RankingTrainerExtensions.cs (2)
47
var options = TrainerExtensionUtil.CreateOptions<
FastTreeRankingTrainer
.Options>(sweepParams, columnInfo.LabelColumnName);
55
property.Add(nameof(
FastTreeRankingTrainer
.Options.RowGroupColumnName), columnInfo.GroupIdColumnName);
Microsoft.ML.FastTree (30)
FastTreeArguments.cs (2)
16
[assembly: EntryPointModule(typeof(
FastTreeRankingTrainer
.Options))]
218
/// Options for the <see cref="
FastTreeRankingTrainer
"/> as used in
FastTreeRanking.cs (16)
20
[assembly: LoadableClass(
FastTreeRankingTrainer
.Summary, typeof(
FastTreeRankingTrainer
), typeof(
FastTreeRankingTrainer
.Options),
22
FastTreeRankingTrainer
.UserNameValue,
23
FastTreeRankingTrainer
.LoadNameValue,
24
FastTreeRankingTrainer
.ShortName,
68
: BoostingFastTreeTrainerBase<
FastTreeRankingTrainer
.Options, RankingPredictionTransformer<FastTreeRankingModelParameters>, FastTreeRankingModelParameters>
85
/// Initializes a new instance of <see cref="
FastTreeRankingTrainer
"/>
111
/// Initializes a new instance of <see cref="
FastTreeRankingTrainer
"/> by using the <see cref="Options"/> class.
479
/// Trains a <see cref="
FastTreeRankingTrainer
"/> using both training and validation data, returns
1025
/// Model parameters for <see cref="
FastTreeRankingTrainer
"/>.
1080
Desc =
FastTreeRankingTrainer
.Summary,
1081
UserName =
FastTreeRankingTrainer
.UserNameValue,
1082
ShortName =
FastTreeRankingTrainer
.ShortName)]
1083
public static CommonOutputs.RankingOutput TrainRanking(IHostEnvironment env,
FastTreeRankingTrainer
.Options input)
1090
return TrainerEntryPointsUtils.Train<
FastTreeRankingTrainer
.Options, CommonOutputs.RankingOutput>(host, input,
Training\Test.cs (2)
421
private readonly
FastTreeRankingTrainer
.LambdaRankObjectiveFunction _rankingObjectiveFunction;
423
public FastNdcgTestForTrainSet(ScoreTracker trainingScores,
FastTreeRankingTrainer
.LambdaRankObjectiveFunction rankingObjectiveFunction, short[] labels, string sortingAlgorithm, int ndcgTruncation)
TreeEnsembleFeaturizationEstimator.cs (4)
395
private readonly
FastTreeRankingTrainer
.Options _trainerOptions;
403
/// The configuration of <see cref="
FastTreeRankingTrainer
"/> used to train the underlying <see cref="TreeEnsembleModelParameters"/>.
405
public
FastTreeRankingTrainer
.Options TrainerOptions;
416
var
trainer = new FastTreeRankingTrainer(Env, _trainerOptions);
TreeTrainersCatalog.cs (6)
127
/// Create a <see cref="
FastTreeRankingTrainer
"/>, which ranks a series of inputs based on their relevancee, using a decision tree ranking model.
145
public static
FastTreeRankingTrainer
FastTree(this RankingCatalog.RankingTrainers catalog,
161
/// Create a <see cref="
FastTreeRankingTrainer
"/> with advanced options, which ranks a series of inputs based on their relevance, using a decision tree ranking model.
172
public static
FastTreeRankingTrainer
FastTree(this RankingCatalog.RankingTrainers catalog,
173
FastTreeRankingTrainer
.Options options)
546
/// Create <see cref="FastTreeRankingFeaturizationEstimator"/>, which uses <see cref="
FastTreeRankingTrainer
"/> to train <see cref="TreeEnsembleModelParameters"/> to create tree-based features.
Microsoft.ML.IntegrationTests (3)
Evaluation.cs (1)
177
.Append(mlContext.Ranking.Trainers.FastTree(new
FastTreeRankingTrainer
.Options { NumberOfThreads = 1 }));
Validation.cs (2)
71
var
trainer = mlContext.Ranking.Trainers.FastTree(new
FastTreeRankingTrainer
.Options()
Microsoft.ML.PerformanceTests (3)
Numeric\Ranking.cs (3)
45
var environment = EnvironmentFactory.CreateRankingEnvironment<RankingEvaluator, TextLoader, HashingTransformer,
FastTreeRankingTrainer
, FastTreeRankingModelParameters>();
99
var environment = EnvironmentFactory.CreateRankingEnvironment<RankingEvaluator, TextLoader, HashingTransformer,
FastTreeRankingTrainer
, FastTreeRankingModelParameters>();
109
var environment = EnvironmentFactory.CreateRankingEnvironment<RankingEvaluator, TextLoader, HashingTransformer,
FastTreeRankingTrainer
, FastTreeRankingModelParameters>();
Microsoft.ML.Samples (4)
Dynamic\Trainers\Ranking\FastTree.cs (1)
30
var
pipeline = mlContext.Ranking.Trainers.FastTree();
Dynamic\Trainers\Ranking\FastTreeWithOptions.cs (2)
31
var options = new
FastTreeRankingTrainer
.Options
44
var
pipeline = mlContext.Ranking.Trainers.FastTree(options);
Dynamic\Transforms\TreeFeaturization\FastTreeRankingFeaturizationWithOptions.cs (1)
46
var trainerOptions = new
FastTreeRankingTrainer
.Options
Microsoft.ML.Tests (3)
TrainerEstimators\TreeEnsembleFeaturizerTest.cs (1)
549
var trainerOptions = new
FastTreeRankingTrainer
.Options
TrainerEstimators\TreeEstimators.cs (2)
175
var
trainer = ML.Ranking.Trainers.FastTree(
176
new
FastTreeRankingTrainer
.Options