2 writes to TrainedEnsemble
Microsoft.ML.LightGbm (2)
LightGbmTrainerBase.cs (2)
430TrainedEnsemble = Booster.GetModel(catBoundaries, modelText); 715TrainedEnsemble = Booster.GetModel(catMetaData.CategoricalBoudaries, bst.GetModelString());
11 references to TrainedEnsemble
Microsoft.ML.LightGbm (11)
LightGbmBinaryTrainer.cs (2)
255Host.Check(TrainedEnsemble != null, "The predictor cannot be created before training is complete"); 257var pred = new LightGbmBinaryModelParameters(Host, TrainedEnsemble, FeatureCount, innerArgs);
LightGbmMulticlassTrainer.cs (5)
197for (int i = classID; i < TrainedEnsemble.NumTrees; i += _numberOfClassesIncludingNan) 200if (TrainedEnsemble.GetTreeAt(i).NumLeaves > 1) 201res.AddTree(TrainedEnsemble.GetTreeAt(i)); 213Host.Check(TrainedEnsemble != null, "The predictor cannot be created before training is complete."); 216Host.Assert(TrainedEnsemble.NumTrees % _numberOfClassesIncludingNan == 0, "Number of trees should be a multiple of number of classes.");
LightGbmRankingTrainer.cs (2)
283Host.Check(TrainedEnsemble != null, "The predictor cannot be created before training is complete"); 285return new LightGbmRankingModelParameters(Host, TrainedEnsemble, FeatureCount, innerArgs);
LightGbmRegressionTrainer.cs (2)
218Host.Check(TrainedEnsemble != null, 221return new LightGbmRegressionModelParameters(Host, TrainedEnsemble, FeatureCount, innerArgs);