1 write to Feature
Microsoft.ML.Core (1)
Data\RoleMappedSchema.cs (1)
177Feature = cols[0];
105 references to Feature
Microsoft.ML.Core (1)
Data\RoleMappedSchema.cs (1)
20/// This class has convenience fields for several common column roles (for example, <see cref="Feature"/>, <see
Microsoft.ML.Data (44)
Evaluators\ClusteringEvaluator.cs (10)
116Host.Assert(schema.Feature.HasValue); 117var t = schema.Feature.Value.Type; 120throw Host.ExceptSchemaMismatch(nameof(schema), "features", schema.Feature.Value.Name, 130Host.Assert(!_calculateDbi || schema.Feature != null); 131return i => _calculateDbi && i == schema.Feature.Value.Index || pred(i); 137Host.Assert(!_calculateDbi || schema.Feature?.Type.IsKnownSizeVector() == true); 142return new Aggregator(Host, schema.Feature, numClusters, _calculateDbi, schema.Weight != null, stratName); 496Host.Assert(schema.Feature.HasValue); 497_featGetter = row.GetGetter<VBuffer<Single>>(schema.Feature.Value); 813string feat = EvaluateUtils.GetColName(_featureCol, schema.Feature, DefaultColumnNames.Features);
Prediction\Calibrator.cs (1)
859if (schema.Feature == null)
Scorers\FeatureContributionCalculation.cs (2)
307private DataViewSchema.Column FeatureColumn => InputRoleMappedSchema.Feature.Value; 319_env.Assert(schema.Feature.HasValue);
Scorers\SchemaBindablePredictorWrapper.cs (21)
127if (schema.Feature?.Type is DataViewType type) 209Contracts.Assert(schema.Feature.HasValue); 222if (!InputRoleMappedSchema.Feature.HasValue || dependingColumns.Count() == 0) 225return Enumerable.Repeat(InputRoleMappedSchema.Feature.Value, 1); 230yield return RoleMappedSchema.ColumnRole.Feature.Bind(InputRoleMappedSchema.Feature.Value.Name); 242getters[0] = _parent.GetPredictionGetter(input, InputRoleMappedSchema.Feature.Value.Index); 329Contracts.Assert(schema.Feature.HasValue); 333var featureToken = ctx.TokenOrNullForName(schema.Feature.Value.Name); 345Contracts.Assert(schema.Feature.HasValue); 348string featName = schema.Feature.Value.Name; 436Contracts.Assert(schema.Feature.HasValue); 440string featureToken = ctx.TokenOrNullForName(schema.Feature.Value.Name); 461if (!schema.Feature.HasValue) 468var featName = schema.Feature.Value.Name; 527if (schema.Feature?.Type is DataViewType typeSrc) 542if (dependingColumns.Count() == 0 || !InputRoleMappedSchema.Feature.HasValue) 545return Enumerable.Repeat(InputRoleMappedSchema.Feature.Value, 1); 550yield return (InputRoleMappedSchema.Feature.HasValue) ? RoleMappedSchema.ColumnRole.Feature.Bind(InputRoleMappedSchema.Feature?.Name) : RoleMappedSchema.ColumnRole.Label.Bind(InputRoleMappedSchema.Label?.Name); 562var featureGetter = InputRoleMappedSchema.Feature.HasValue ? input.GetGetter<VBuffer<float>>(InputRoleMappedSchema.Feature.Value) : null;
Training\TrainerUtils.cs (10)
53if (!data.Schema.Feature.HasValue) 55var col = data.Schema.Feature.Value; 70Contracts.Assert(data.Schema.Feature.HasValue); 71var col = data.Schema.Feature.Value; 235if ((opt & CursOpt.Features) != 0 && data.Schema.Feature.HasValue) 236columns.Add(data.Schema.Feature.Value); 267Contracts.CheckParam(schema.Feature.HasValue, nameof(schema), "Missing feature column"); 269return row.GetGetter<VBuffer<float>>(schema.Feature.Value); 429if (tschema.Feature?.Name is string fname && fname != DefaultColumnNames.Features) 834if ((opt & CursOpt.Features) != 0 && data.Schema.Feature != null)
Microsoft.ML.Ensemble (3)
EnsembleUtils.cs (2)
22Contracts.Assert(data.Schema.Feature.HasValue); 24var featCol = data.Schema.Feature.Value;
Selector\FeatureSelector\RandomFeatureSelector.cs (1)
52var type = data.Schema.Feature.Value.Type;
Microsoft.ML.EntryPoints (2)
PermutationFeatureImportance.cs (2)
65Contracts.Check(roleMappedData.Schema.Feature != null, "Feature column not found."); 310schema.Feature.Value.GetSlotNames(ref slots);
Microsoft.ML.FastTree (26)
FastTree.cs (5)
190AnnotationUtils.TryGetCategoricalFeatureIndices(trainData.Schema.Schema, trainData.Schema.Feature.Value.Index, out CategoricalFeatures); 205Host.Assert(data.Schema.Feature.HasValue); 211return itdv?.GetSlotType(data.Schema.Feature.Value.Index) != null; 1329Host.Assert(examples.Schema.Feature.HasValue); 1364int featIdx = AddColumnIfNeeded(examples.Schema.Feature, toTranspose);
FastTreeClassification.cs (1)
197FeatureCount = trainData.Schema.Feature.Value.Type.GetValueCount();
FastTreeRanking.cs (1)
150FeatureCount = trainData.Schema.Feature.Value.Type.GetValueCount();
FastTreeRegression.cs (1)
120FeatureCount = trainData.Schema.Feature.Value.Type.GetValueCount();
FastTreeTweedie.cs (1)
130FeatureCount = trainData.Schema.Feature.Value.Type.GetValueCount();
GamModelParameters.cs (1)
634var featCol = schema.Feature.Value;
GamTrainer.cs (3)
233InputLength = context.TrainingSet.Schema.Feature.Value.Type.GetValueCount(); 270Host.Assert(data.Schema.Feature.HasValue); 274return (data.Data as ITransposeDataView)?.GetSlotType(data.Schema.Feature.Value.Index) != null;
RandomForestClassification.cs (1)
224FeatureCount = trainData.Schema.Feature.Value.Type.GetValueCount();
RandomForestRegression.cs (1)
363FeatureCount = trainData.Schema.Feature.Value.Type.GetValueCount();
TreeEnsemble\InternalTreeEnsemble.cs (2)
440Contracts.Assert(schema.Feature.HasValue); 441var feat = schema.Feature.Value;
TreeEnsembleFeaturizer.cs (9)
80private DataViewSchema.Column FeatureColumn => InputRoleMappedSchema.Feature.Value; 110ectx.Assert(schema.Feature.HasValue); 526env.CheckParam(schema.Feature != null, nameof(schema), "Need a feature column"); 646Contracts.Assert(data.Schema.Feature.HasValue); 655if (vm.InputType.GetVectorSize() != data.Schema.Feature.Value.Type.GetVectorSize()) 659vm.InputType.GetVectorSize(), data.Schema.Feature.Value.Type.GetVectorSize()); 716ch.Assert(data.Schema.Feature.HasValue); 726if (data != null && vm.InputType.GetVectorSize() != data.Schema.Feature.Value.Type.GetVectorSize()) 730vm.InputType.GetVectorSize(), data.Schema.Feature.Value.Type.GetVectorSize());
Microsoft.ML.LightGbm (2)
LightGbmTrainerBase.cs (2)
645var featureCol = trainData.Schema.Feature.Value; 648var colType = trainData.Schema.Feature.Value.Type;
Microsoft.ML.Mkl.Components (5)
OlsLinearRegression.cs (2)
157ch.CheckParam(examples.Schema.Feature.HasValue, nameof(examples), "Need a feature column"); 166var typeFeat = examples.Schema.Feature.Value.Type as VectorDataViewType;
SymSgdClassificationTrainer.cs (3)
209ch.Assert(examplesToFeedTrain.Schema.Feature.HasValue); 213ch.Check(examplesToFeedTrain.Schema.Feature.Value.Type is VectorDataViewType vecType && vecType.Size > 0, "Training set has no features, aborting training."); 703int numFeatures = data.Schema.Feature.Value.Type.GetVectorSize();
Microsoft.ML.StandardTrainers (16)
LdSvm\LdSvmTrainer.cs (3)
591using (var cursor = _data.Data.GetRowCursor(_data.Data.Schema[_data.Schema.Feature.Value.Name])) 593var getter = cursor.GetGetter<VBuffer<float>>(_data.Data.Schema[_data.Schema.Feature.Value.Name]); 632var featureCol = _data.Data.Schema[_data.Schema.Feature.Value.Name];
Standard\LinearModelParameters.cs (2)
532Statistics?.SaveText(writer, schema.Feature.Value, 20); 543Statistics?.SaveSummaryInKeyValuePairs(schema.Feature.Value, int.MaxValue, results);
Standard\LogisticRegression\LbfgsPredictorBase.cs (1)
487var typeFeat = data.Schema.Feature.Value.Type as VectorDataViewType;
Standard\LogisticRegression\LogisticRegression.cs (1)
268var featureCol = cursorFactory.Data.Schema.Feature.Value;
Standard\LogisticRegression\MulticlassLogisticRegression.cs (1)
883Statistics.SaveText(writer, schema.Feature.Value, 20);
Standard\MulticlassClassification\MulticlassNaiveBayesTrainer.cs (1)
141Host.Check(data.Schema.Feature.HasValue, "Missing Feature column");
Standard\SdcaBinary.cs (5)
120ch.Assert(examplesToFeedTrain.Schema.Feature.HasValue); 124ch.Check(examplesToFeedTrain.Schema.Feature.Value.Type is VectorDataViewType vecType && vecType.Size > 0, "Training set has no features, aborting training."); 327int numFeatures = data.Schema.Feature.Value.Type.GetVectorSize(); 2024Contracts.Assert(data.Schema.Feature.HasValue); 2026int numFeatures = data.Schema.Feature.Value.Type.GetVectorSize();
Standard\StochasticTrainerBase.cs (2)
84ch.Assert(examplesToFeedTrain.Schema.Feature.HasValue); 88ch.Check(examplesToFeedTrain.Schema.Feature.Value.Type is VectorDataViewType vecType && vecType.Size > 0, "Training set has no features, aborting training.");
Microsoft.ML.TimeSeries (6)
AdaptiveSingularSpectrumSequenceModeler.cs (6)
1210_host.CheckParam(data.Schema.Feature.HasValue, nameof(data), "Must have features column."); 1211var featureCol = data.Schema.Feature.Value; 1557if (data.Schema.Feature.Value.Type != NumberDataViewType.Single) 1558throw _host.ExceptUserArg(nameof(data.Schema.Feature.Value.Name), "The time series input column has " + 1559"type '{0}', but must be a float.", data.Schema.Feature.Value.Type); 1561var col = data.Schema.Feature.Value;