1 write to GbmOptions
Microsoft.ML.LightGbm (1)
LightGbmTrainerBase.cs (1)
356GbmOptions = LightGbmTrainerOptions.ToDictionary(Host);
26 references to GbmOptions
Microsoft.ML.LightGbm (26)
LightGbmBinaryTrainer.cs (2)
256var innerArgs = LightGbmInterfaceUtils.JoinParameters(base.GbmOptions); 280=> GbmOptions["objective"] = "binary";
LightGbmMulticlassTrainer.cs (7)
218var innerArgs = LightGbmInterfaceUtils.JoinParameters(GbmOptions); 320int numberOfLeaves = (int)GbmOptions["num_leaves"]; 322GbmOptions["min_data_per_leaf"] = minimumExampleCountPerLeaf; 326ch.Info("Auto-tuning parameters: " + nameof(LightGbmTrainerOptions.LearningRate) + " = " + GbmOptions["learning_rate"]); 339GbmOptions["num_class"] = _numberOfClassesIncludingNan; 353GbmOptions["objective"] = "multiclass"; 355GbmOptions["objective"] = "multiclassova";
LightGbmRankingTrainer.cs (3)
284var innerArgs = LightGbmInterfaceUtils.JoinParameters(GbmOptions); 291GbmOptions["objective"] = "lambdarank"; 295GbmOptions["eval_at"] = "5";
LightGbmRegressionTrainer.cs (2)
220var innerArgs = LightGbmInterfaceUtils.JoinParameters(GbmOptions); 243GbmOptions["objective"] = "regression";
LightGbmTrainerBase.cs (12)
389GbmOptions["objective"] = split[0].Split('=')[1]; 472GbmOptions["tree_learner"] = ParallelTraining.ParallelType(); 477GbmOptions[pair.Key] = pair.Value; 510GbmOptions["learning_rate"] = learningRate; 511GbmOptions["num_leaves"] = numberOfLeaves; 512GbmOptions["min_data_per_leaf"] = minimumExampleCountPerLeaf; 525internal Dictionary<string, object> GetGbmParameters() => GbmOptions; 637GbmOptions["categorical_feature"] = string.Join(",", catIndices); 657string param = LightGbmInterfaceUtils.JoinParameters(GbmOptions); 704ch.Assert(((ITrainer)this).PredictionKind != PredictionKind.MulticlassClassification || GbmOptions.ContainsKey("num_class"), 710ch.Info("LightGBM objective={0}", GbmOptions["objective"]); 711using (Booster bst = WrappedLightGbmTraining.Train(Host, ch, pch, GbmOptions, dtrain,