1 write to Data
Microsoft.ML.Core (1)
Data\RoleMappedSchema.cs (1)
427
Data
= data;
78 references to Data
Microsoft.ML.Core (2)
Data\RoleMappedSchema.cs (2)
406
/// guaranteed to equal the the <see cref="IDataView.Schema"/> of <see cref="
Data
"/>.
418
/// guaranteed to be the same as <see cref="
Data
"/>'s <see cref="IDataView.Schema"/>.
Microsoft.ML.Data (24)
Commands\CrossValidationCommand.cs (3)
258
var pipe = ApplyTransformUtils.ApplyAllTransformsToData(env, srcData.
Data
, dstData, marker);
533
IDataScorerTransform scorePipe = scorerComp.CreateComponent(host, testData.
Data
, mapper, trainData.Schema);
543
(e, newSource) => ApplyTransformUtils.ApplyAllTransformsToData(e, trainData.
Data
, newSource)),
Commands\ScoreCommand.cs (1)
244
return sc.CreateComponent(env, data.
Data
, mapper, trainSchema);
Commands\TrainCommand.cs (3)
363
var dataPipe = data.
Data
;
498
bool shouldCache = cacheData ?? !(data.
Data
is BinaryLoader) && trainer.Info.WantCaching;
504
var cacheView = new CacheDataView(env, data.
Data
, prefetch);
EntryPoints\InputBase.cs (2)
97
outputData = new CacheDataView(host, roleMappedData.
Data
, null);
105
outputData = new CacheDataView(host, roleMappedData.
Data
, null);
EntryPoints\PredictorModelImpl.cs (1)
36
TransformModel = new TransformModelImpl(env, trainingData.
Data
, startingData);
Evaluators\AnomalyDetectionEvaluator.cs (1)
114
return NopTransform.CreateIfNeeded(Host, data.
Data
);
Evaluators\EvaluatorBase.cs (2)
38
var dict = ProcessData(data.
Data
, data.Schema, activeCols, agg, dictionaries);
460
return new RowToRowMapperTransform(Host, data.
Data
, mapper, null);
Evaluators\MamlEvaluator.cs (4)
109
data = new RoleMappedData(data.
Data
, GetInputColumnRoles(data.Schema, needStrat: true));
223
var dataEval = new RoleMappedData(scoredData.
Data
, GetInputColumnRoles(schema));
229
var idv = perInst.
Data
;
284
var data = new RoleMappedData(perInstance.
Data
, GetInputColumnRoles(perInstance.Schema, needName: true));
Evaluators\RankingEvaluator.cs (1)
141
return new RankingPerInstanceTransform(Host, data.
Data
,
Prediction\Calibrator.cs (1)
2223
calibratedPredictor = scp.Calibrate(ch, data.
Data
, calibratorTrainer, input.MaxRows);
Training\TrainerUtils.cs (4)
231
data.
Data
.Schema.Where(c => extraCols.Contains(c.Index)).ToList();
249
=> data.
Data
.GetRowCursor(CreatePredicate(data, opt, extraCols), rand);
257
=> data.
Data
.GetRowCursorSet(CreatePredicate(data, opt, extraCols), n, rand);
442
var data = context.TrainingSet.
Data
;
Utilities\ComponentCreation.cs (1)
173
return CreateCore<IDataScorerTransform>(env, factoryType, signatureType, settings, data.
Data
, mapper, trainSchema);
Microsoft.ML.Ensemble (7)
EnsembleUtils.cs (1)
36
host, "FeatureSelector", data.
Data
, name, name, type, type,
Selector\SubsetSelector\BaseSubsetSelector.cs (2)
73
string name = Data.
Data
.Schema.GetTempColumnName();
77
var view = new GenerateNumberTransform(Host, args, Data.
Data
);
Selector\SubsetSelector\BootstrapSelector.cs (1)
51
var viewTrain = new BootstrapSamplingTransformer(Host, new BootstrapSamplingTransformer.Options(), Data.
Data
);
Selector\SubsetSelector\RandomPartitionSelector.cs (2)
40
string name = Data.
Data
.Schema.GetTempColumnName();
44
IDataTransform view = new GenerateNumberTransform(Host, args, Data.
Data
);
Trainer\EnsembleTrainerBase.cs (1)
159
Trainers[(int)index].Fit(subset.Data.
Data
).Model,
Microsoft.ML.EntryPoints (10)
PermutationFeatureImportance.cs (8)
94
env, predictor as IPredictorProducing<float>, roleMappedData.
Data
.Schema, featureColumnName);
98
roleMappedData.
Data
,
151
env, predictor as IPredictorProducing<VBuffer<float>>, roleMappedData.
Data
.Schema, featureColumnName, labelColumnName);
155
roleMappedData.
Data
,
210
env, predictor as IPredictorProducing<float>, roleMappedData.
Data
.Schema, featureColumnName);
214
roleMappedData.
Data
,
263
env, predictor as IPredictorProducing<float>, roleMappedData.
Data
.Schema, featureColumnName);
267
roleMappedData.
Data
,
ScoreModel.cs (2)
87
scoredPipe = scorer.CreateComponent(host, data.
Data
, mapper, input.PredictorModel.GetTrainingSchema(host));
137
scoredPipe = scorer.CreateComponent(host, data.
Data
, mapper, input.PredictorModel.GetTrainingSchema(host));
Microsoft.ML.FastTree (5)
FastTree.cs (3)
210
var itdv = data.
Data
as ITransposeDataView;
1342
IDataView data = examples.
Data
;
1815
double rowCountDbl = (double?)_data.
Data
.GetRowCount() ?? double.NaN;
GamTrainer.cs (1)
274
return (data.
Data
as ITransposeDataView)?.GetSlotType(data.Schema.Feature.Value.Index) != null;
TreeEnsembleFeaturizer.cs (1)
735
return new GenericScorer(env, scorerArgs, data.
Data
, bound, data.Schema);
Microsoft.ML.Mkl.Components (1)
SymSgdClassificationTrainer.cs (1)
189
var idvToShuffle = examples.
Data
;
Microsoft.ML.Recommender (2)
MatrixFactorizationTrainer.cs (2)
474
using (var cursor = data.
Data
.GetRowCursor(matrixColumnIndexColInfo, matrixRowIndexColInfo, data.Schema.Label.Value))
493
using (var validCursor = validData.
Data
.GetRowCursor(matrixColumnIndexColInfo, matrixRowIndexColInfo, data.Schema.Label.Value))
Microsoft.ML.StandardTrainers (21)
FactorizationMachine\FactorizationMachineTrainer.cs (3)
377
using (var cursor = data.
Data
.GetRowCursor(columns))
451
if (shuffle && !data.
Data
.CanShuffle)
489
using (var cursor = data.
Data
.GetRowCursor(columns, rng))
LdSvm\LdSvmTrainer.cs (7)
573
using (var cursor = _data.
Data
.GetRowCursor())
591
using (var cursor = _data.
Data
.GetRowCursor(_data.
Data
.Schema[_data.Schema.Feature.Value.Name]))
593
var getter = cursor.GetGetter<VBuffer<float>>(_data.
Data
.Schema[_data.Schema.Feature.Value.Name]);
632
var featureCol = _data.
Data
.Schema[_data.Schema.Feature.Value.Name];
633
var labelCol = _data.
Data
.Schema[_data.Schema.Label.Value.Name];
634
using (var cursor = _data.
Data
.GetRowCursor(featureCol, labelCol))
Standard\LogisticRegression\LbfgsPredictorBase.cs (1)
604
Double totalCount = data.
Data
.GetRowCount() ?? Double.NaN;
Standard\LogisticRegression\LogisticRegression.cs (1)
269
var schema = cursorFactory.Data.
Data
.Schema;
Standard\MulticlassClassification\MetaMulticlassTrainer.cs (3)
100
IDataView dataView = data.
Data
;
102
dataView = new NAFilter(Host, data.
Data
, false, label.Name);
104
return LambdaColumnMapper.Create(Host, "Label mapper", data.
Data
,
Standard\MulticlassClassification\OneVersusAllTrainer.cs (1)
185
return new BinaryPredictionTransformer<TScalarPredictor>(Host, calibratedModel, trainedData.
Data
.Schema, transformer.FeatureColumnName);
Standard\MulticlassClassification\PairwiseCouplingTrainer.cs (1)
161
return new BinaryPredictionTransformer<TDistPredictor>(Host, calibratedModel, trainedData.
Data
.Schema, transformer.FeatureColumnName);
Standard\Online\OnlineLinear.cs (1)
316
if (shuffle && !data.
Data
.CanShuffle)
Standard\SdcaBinary.cs (1)
100
var idvToShuffle = examples.
Data
;
Standard\Simple\SimpleTrainers.cs (1)
268
using (var cursor = data.
Data
.GetRowCursor(cols))
Standard\StochasticTrainerBase.cs (1)
64
var idvToShuffle = examples.
Data
;
Microsoft.ML.TimeSeries (3)
AdaptiveSingularSpectrumSequenceModeler.cs (3)
1218
using (var cursor = data.
Data
.GetRowCursor(featureCol))
1562
using (var cursor = data.
Data
.GetRowCursor(data.
Data
.Schema))
Microsoft.ML.Vision (3)
ImageClassificationTrainer.cs (3)
664
InitializeTrainingGraph(trainContext.TrainingSet.
Data
);
666
var validationSet = trainContext.ValidationSet?.
Data
?? _options.ValidationSet;
696
CacheFeaturizedImagesToDisk(trainContext.TrainingSet.
Data
, _options.LabelColumnName,