1 write to FeatureColumn
Microsoft.ML.Data (1)
Training\TrainerEstimatorBase.cs (1)
67FeatureColumn = feature;
35 references to FeatureColumn
Microsoft.ML.Data (7)
Training\TrainerEstimatorBase.cs (7)
108if (!inputSchema.TryFindColumn(FeatureColumn.Name, out var featureCol)) 109throw Host.ExceptSchemaMismatch(nameof(inputSchema), "feature", FeatureColumn.Name); 110if (!FeatureColumn.IsCompatibleWith(featureCol)) 111throw Host.ExceptSchemaMismatch(nameof(inputSchema), "feature", FeatureColumn.Name, 112FeatureColumn.GetTypeString(), featureCol.GetTypeString()); 166new RoleMappedData(data, label: LabelColumn.Name, feature: FeatureColumn.Name, weight: WeightColumn.Name); 198new RoleMappedData(data, label: LabelColumn.Name, feature: FeatureColumn.Name, group: GroupIdColumn.Name, weight: WeightColumn.Name);
Microsoft.ML.FastTree (8)
FastTreeClassification.cs (1)
303=> new BinaryPredictionTransformer<CalibratedModelParametersBase<FastTreeBinaryModelParameters, PlattCalibrator>>(Host, model, trainSchema, FeatureColumn.Name);
FastTreeRanking.cs (1)
476=> new RankingPredictionTransformer<FastTreeRankingModelParameters>(Host, model, trainSchema, FeatureColumn.Name);
FastTreeRegression.cs (1)
192=> new RegressionPredictionTransformer<FastTreeRegressionModelParameters>(Host, model, trainSchema, FeatureColumn.Name);
FastTreeTweedie.cs (1)
351=> new RegressionPredictionTransformer<FastTreeTweedieModelParameters>(Host, model, trainSchema, FeatureColumn.Name);
GamClassification.cs (1)
174=> new BinaryPredictionTransformer<CalibratedModelParametersBase<GamBinaryModelParameters, PlattCalibrator>>(Host, model, trainSchema, FeatureColumn.Name);
GamRegression.cs (1)
126=> new RegressionPredictionTransformer<GamRegressionModelParameters>(Host, model, trainSchema, FeatureColumn.Name);
RandomForestClassification.cs (1)
366=> new BinaryPredictionTransformer<FastForestBinaryModelParameters>(Host, model, trainSchema, FeatureColumn.Name);
RandomForestRegression.cs (1)
495=> new RegressionPredictionTransformer<FastForestRegressionModelParameters>(Host, model, trainSchema, FeatureColumn.Name);
Microsoft.ML.LightGbm (4)
LightGbmBinaryTrainer.cs (1)
294=> new BinaryPredictionTransformer<CalibratedModelParametersBase<LightGbmBinaryModelParameters, PlattCalibrator>>(Host, model, trainSchema, FeatureColumn.Name);
LightGbmMulticlassTrainer.cs (1)
376=> new MulticlassPredictionTransformer<OneVersusAllModelParameters>(Host, model, trainSchema, FeatureColumn.Name, LabelColumn.Name);
LightGbmRankingTrainer.cs (1)
307=> new RankingPredictionTransformer<LightGbmRankingModelParameters>(Host, model, trainSchema, FeatureColumn.Name);
LightGbmRegressionTrainer.cs (1)
255=> new RegressionPredictionTransformer<LightGbmRegressionModelParameters>(Host, model, trainSchema, FeatureColumn.Name);
Microsoft.ML.Mkl.Components (2)
OlsLinearRegression.cs (1)
132=> new RegressionPredictionTransformer<OlsModelParameters>(Host, model, trainSchema, FeatureColumn.Name);
SymSgdClassificationTrainer.cs (1)
263=> new BinaryPredictionTransformer<TPredictor>(Host, model, trainSchema, FeatureColumn.Name);
Microsoft.ML.StandardTrainers (13)
Standard\LogisticRegression\LbfgsPredictorBase.cs (1)
241options.FeatureColumnName = FeatureColumn.Name;
Standard\LogisticRegression\LogisticRegression.cs (1)
181=> new BinaryPredictionTransformer<CalibratedModelParametersBase<LinearBinaryModelParameters, PlattCalibrator>>(Host, model, trainSchema, FeatureColumn.Name);
Standard\LogisticRegression\MulticlassLogisticRegression.cs (1)
384=> new MulticlassPredictionTransformer<MaximumEntropyModelParameters>(Host, model, trainSchema, FeatureColumn.Name, LabelColumn.Name);
Standard\MulticlassClassification\MulticlassNaiveBayesTrainer.cs (1)
130=> new MulticlassPredictionTransformer<NaiveBayesMulticlassModelParameters>(Host, model, trainSchema, FeatureColumn.Name, LabelColumn.Name);
Standard\Online\AveragedPerceptron.cs (1)
218=> new BinaryPredictionTransformer<LinearBinaryModelParameters>(Host, model, trainSchema, FeatureColumn.Name);
Standard\Online\LinearSvm.cs (1)
338=> new BinaryPredictionTransformer<LinearBinaryModelParameters>(Host, model, trainSchema, FeatureColumn.Name);
Standard\Online\OnlineGradientDescent.cs (1)
203=> new RegressionPredictionTransformer<LinearRegressionModelParameters>(Host, model, trainSchema, FeatureColumn.Name);
Standard\PoissonRegression\PoissonRegression.cs (1)
128=> new RegressionPredictionTransformer<PoissonRegressionModelParameters>(Host, model, trainSchema, FeatureColumn.Name);
Standard\SdcaBinary.cs (2)
1551=> new BinaryPredictionTransformer<TModelParameters>(Host, model, trainSchema, FeatureColumn.Name); 2008=> new BinaryPredictionTransformer<TModel>(Host, model, trainSchema, FeatureColumn.Name);
Standard\SdcaMulticlass.cs (2)
566new MulticlassPredictionTransformer<MaximumEntropyModelParameters>(Host, model, trainSchema, FeatureColumn.Name, LabelColumn.Name); 663new MulticlassPredictionTransformer<LinearMulticlassModelParameters>(Host, model, trainSchema, FeatureColumn.Name, LabelColumn.Name);
Standard\SdcaRegression.cs (1)
202=> new RegressionPredictionTransformer<LinearRegressionModelParameters>(Host, model, trainSchema, FeatureColumn.Name);
Microsoft.ML.Vision (1)
ImageClassificationTrainer.cs (1)
652FeatureColumn.Name, LabelColumn.Name, _options.ScoreColumnName, _options.PredictedLabelColumnName);