4 instantiations of LightGbmRankingTrainer
Microsoft.ML.LightGbm (4)
LightGbmCatalog.cs (3)
186return new LightGbmRankingTrainer(env, labelColumnName, featureColumnName, rowGroupColumnName, exampleWeightColumnName, 207return new LightGbmRankingTrainer(env, options); 223return new LightGbmRankingTrainer(env, lightGbmModel, featureColumnName);
LightGbmRankingTrainer.cs (1)
334() => new LightGbmRankingTrainer(host, input),
32 references to LightGbmRankingTrainer
Microsoft.ML.AutoML (3)
API\RankingExperiment.cs (1)
65/// See <see cref="LightGbmRankingTrainer"/>.
TrainerExtensions\RankingTrainerExtensions.cs (2)
24LightGbmRankingTrainer.Options options = TrainerExtensionUtil.CreateLightGbmOptions<LightGbmRankingTrainer.Options,
Microsoft.ML.LightGbm (24)
LightGbmCatalog.cs (7)
156/// Create <see cref="LightGbmRankingTrainer"/>, which predicts a target using a gradient boosting decision tree ranking model. 174public static LightGbmRankingTrainer LightGbm(this RankingCatalog.RankingTrainers catalog, 191/// Create <see cref="LightGbmRankingTrainer"/> with advanced options, which predicts a target using a gradient boosting decision tree ranking model. 202public static LightGbmRankingTrainer LightGbm(this RankingCatalog.RankingTrainers catalog, 203LightGbmRankingTrainer.Options options) 211/// Create <see cref="LightGbmRankingTrainer"/> from a pre-trained LightGBM model, which predicts a target using a gradient boosting decision tree ranking model. 216public static LightGbmRankingTrainer LightGbm(this RankingCatalog.RankingTrainers catalog,
LightGbmMulticlassTrainer.cs (1)
175/// Initializes a new instance of <see cref="LightGbmRankingTrainer"/>
LightGbmRankingTrainer.cs (16)
17[assembly: LoadableClass(LightGbmRankingTrainer.UserName, typeof(LightGbmRankingTrainer), typeof(LightGbmRankingTrainer.Options), 19"LightGBM Ranking", LightGbmRankingTrainer.LoadNameValue, LightGbmRankingTrainer.ShortName, DocName = "trainer/LightGBM.md")] 28/// Model parameters for <see cref="LightGbmRankingTrainer"/>. 101/// <seealso cref="LightGbmExtensions.LightGbm(RankingCatalog.RankingTrainers, LightGbmRankingTrainer.Options)"/> 103public sealed class LightGbmRankingTrainer : LightGbmTrainerBase<LightGbmRankingTrainer.Options, 115/// Options for the <see cref="LightGbmRankingTrainer"/> as used in 183/// Initializes a new instance of <see cref="LightGbmRankingTrainer"/> 220/// Initializes a new instance of <see cref="LightGbmRankingTrainer"/> 310/// Trains a <see cref="LightGbmRankingTrainer"/> using both training and validation data, returns 324UserName = LightGbmRankingTrainer.UserName, 325ShortName = LightGbmRankingTrainer.ShortName)] 326public static CommonOutputs.RankingOutput TrainRanking(IHostEnvironment env, LightGbmRankingTrainer.Options input) 333return TrainerEntryPointsUtils.Train<LightGbmRankingTrainer.Options, CommonOutputs.RankingOutput>(host, input,
Microsoft.ML.Samples (3)
Dynamic\Trainers\Ranking\LightGbm.cs (1)
30var pipeline = mlContext.Ranking.Trainers.LightGbm();
Dynamic\Trainers\Ranking\LightGbmWithOptions.cs (2)
31var options = new LightGbmRankingTrainer.Options 45var pipeline = mlContext.Ranking.Trainers.LightGbm(options);
Microsoft.ML.Tests (2)
TrainerEstimators\TreeEstimators.cs (2)
199var trainer = ML.Ranking.Trainers.LightGbm(new LightGbmRankingTrainer.Options() { LabelColumnName = "Label0", FeatureColumnName = "NumericFeatures", RowGroupColumnName = "Group", LearningRate = 0.4 });