2 writes to TrainSchema
Microsoft.ML.Data (2)
Scorers\PredictionTransformer.cs (2)
91
TrainSchema
= trainSchema;
131
TrainSchema
= loader.Schema;
33 references to TrainSchema
Microsoft.ML.Data (17)
Scorers\PredictionTransformer.cs (15)
180
DataSaverUtils.SaveDataView(ch, saver, new EmptyDataView(Host,
TrainSchema
), writer.BaseStream);
248
else if (!
TrainSchema
.TryGetColumnIndex(FeatureColumnName, out int col))
251
FeatureColumnType =
TrainSchema
[col].Type;
263
else if (!
TrainSchema
.TryGetColumnIndex(FeatureColumnName, out int col))
266
FeatureColumnType =
TrainSchema
[col].Type;
306
var schema = new RoleMappedSchema(
TrainSchema
, null, FeatureColumnName);
307
return new GenericScorer(Host, new GenericScorer.Arguments(), new EmptyDataView(Host,
TrainSchema
), BindableMapper.Bind(Host, schema), schema);
348
var schema = new RoleMappedSchema(
TrainSchema
, null, FeatureColumnName);
350
Scorer = new BinaryClassifierScorer(Host, args, new EmptyDataView(Host,
TrainSchema
), BindableMapper.Bind(Host, schema), schema);
440
var schema = new RoleMappedSchema(
TrainSchema
, LabelColumnName, FeatureColumnName);
442
Scorer = new BinaryClassifierScorer(Host, args, new EmptyDataView(Host,
TrainSchema
), BindableMapper.Bind(Host, schema), schema);
532
var schema = new RoleMappedSchema(
TrainSchema
, _trainLabelColumn, FeatureColumnName);
534
Scorer = new MulticlassClassificationScorer(Host, args, new EmptyDataView(Host,
TrainSchema
), BindableMapper.Bind(Host, schema), schema);
686
var schema = new RoleMappedSchema(
TrainSchema
, null, FeatureColumnName);
688
Scorer = new ClusteringScorer(Host, args, new EmptyDataView(Host,
TrainSchema
), BindableMapper.Bind(Host, schema), schema);
TrainCatalog.cs (2)
296
return new BinaryPredictionTransformer<TModel>(Environment, model.Model, model.
TrainSchema
, model.FeatureColumnName, threshold, model.ThresholdColumn);
790
return new AnomalyPredictionTransformer<TModel>(Environment, model.Model, model.
TrainSchema
, model.FeatureColumnName, threshold, model.ThresholdColumn);
Microsoft.ML.FastTree (4)
TreeEnsembleFeaturizationTransformer.cs (4)
116
_featureDetachedColumn = new DataViewSchema.DetachedColumn(
TrainSchema
[featureColumnName]);
134
var roleMappedSchema = MakeFeatureRoleMappedSchema(
TrainSchema
);
135
Scorer = new GenericScorer(Host, _scorerArgs, new EmptyDataView(Host,
TrainSchema
), BindableMapper.Bind(Host, roleMappedSchema), roleMappedSchema);
168
DataSaverUtils.SaveDataView(ch, saver, new EmptyDataView(Host,
TrainSchema
), writer.BaseStream);
Microsoft.ML.Recommender (7)
MatrixFactorizationPredictor.cs (7)
474
var schema = new RoleMappedSchema(
TrainSchema
, roles);
493
if (!
TrainSchema
.TryGetColumnIndex(MatrixColumnIndexColumnName, out int xCol))
495
MatrixColumnIndexColumnType =
TrainSchema
[xCol].Type;
497
if (!
TrainSchema
.TryGetColumnIndex(MatrixRowIndexColumnName, out int yCol))
499
MatrixRowIndexColumnType =
TrainSchema
[yCol].Type;
505
Scorer = new GenericScorer(Host, args, new EmptyDataView(Host,
TrainSchema
), BindableMapper.Bind(Host, schema), schema);
541
DataSaverUtils.SaveDataView(ch, saver, new EmptyDataView(Host,
TrainSchema
), writer.BaseStream);
Microsoft.ML.StandardTrainers (5)
FactorizationMachine\FieldAwareFactorizationMachineModelParameters.cs (5)
350
if (!
TrainSchema
.TryGetColumnIndex(featureColumns[i], out int col))
352
featureColumnTypes[i] =
TrainSchema
[col].Type;
364
Scorer = new BinaryClassifierScorer(Host, args, new EmptyDataView(Host,
TrainSchema
), BindableMapper.Bind(Host, schema), schema);
410
DataSaverUtils.SaveDataView(ch, saver, new EmptyDataView(Host,
TrainSchema
), writer.BaseStream);
427
var schema = new RoleMappedSchema(
TrainSchema
, roles);