TrainingSet

1 write to TrainingSet

Microsoft.ML.Core (1)

Prediction\TrainContext.cs (1)

62TrainingSet = trainingSet;

32 references to TrainingSet

Microsoft.ML.Core (1)

Prediction\TrainContext.cs (1)

49/// <param name="trainingSet">Will set <see cref="TrainingSet"/> to this value. This must be specified</param>

Microsoft.ML.Data (2)

Training\TrainerUtils.cs (2)

427var tschema = context.TrainingSet.Schema; 442var data = context.TrainingSet.Data;

Microsoft.ML.Ensemble (1)

Trainer\EnsembleTrainerBase.cs (1)

114return TrainCore(ch, context.TrainingSet);

Microsoft.ML.FastTree (8)

FastTreeClassification.cs (1)

187var trainData = context.TrainingSet;

FastTreeRanking.cs (1)

141var trainData = context.TrainingSet;

FastTreeRegression.cs (1)

111var trainData = context.TrainingSet;

FastTreeTweedie.cs (1)

120var trainData = context.TrainingSet;

GamTrainer.cs (2)

227ConvertData(context.TrainingSet, context.ValidationSet); 233InputLength = context.TrainingSet.Schema.Feature.Value.Type.GetValueCount();

RandomForestClassification.cs (1)

214var trainData = context.TrainingSet;

RandomForestRegression.cs (1)

353var trainData = context.TrainingSet;

Microsoft.ML.KMeansClustering (1)

KMeansPlusPlusTrainer.cs (1)

200var data = context.TrainingSet;

Microsoft.ML.LightGbm (1)

LightGbmTrainerBase.cs (1)

466dtrain = LoadTrainingData(ch, context.TrainingSet, out catMetaData);

Microsoft.ML.Mkl.Components (2)

OlsLinearRegression.cs (1)

156var examples = context.TrainingSet;

SymSgdClassificationTrainer.cs (1)

230var preparedData = PrepareDataFromTrainingExamples(ch, context.TrainingSet, out int weightSetCount);

Microsoft.ML.PCA (2)

PcaTrainer.cs (2)

190context.TrainingSet.CheckFeatureFloatVector(out int dimension); 194return TrainCore(ch, context.TrainingSet, dimension);

Microsoft.ML.Recommender (1)

MatrixFactorizationTrainer.cs (1)

428return TrainCore(ch, context.TrainingSet, context.ValidationSet);

Microsoft.ML.StandardTrainers (11)

FactorizationMachine\FactorizationMachineTrainer.cs (1)

563return TrainCore(ch, pch, context.TrainingSet, context.ValidationSet, initPredictor);

LdSvm\LdSvmTrainer.cs (3)

194trainContext.TrainingSet.CheckFeatureFloatVector(out var numFeatures); 195trainContext.TrainingSet.CheckBinaryLabel(); 198return TrainCore(ch, trainContext.TrainingSet, numLeaf, numFeatures);

Standard\LogisticRegression\LbfgsPredictorBase.cs (1)

438var data = context.TrainingSet;

Standard\MulticlassClassification\MetaMulticlassTrainer.cs (1)

120var data = context.TrainingSet;

Standard\MulticlassClassification\MulticlassNaiveBayesTrainer.cs (1)

135var data = context.TrainingSet;

Standard\Online\OnlineLinear.cs (1)

288var data = context.TrainingSet;

Standard\SdcaBinary.cs (1)

74var preparedData = PrepareDataFromTrainingExamples(ch, context.TrainingSet, out int weightSetCount);

Standard\Simple\SimpleTrainers.cs (1)

253var data = context.TrainingSet;

Standard\StochasticTrainerBase.cs (1)

35var preparedData = PrepareDataFromTrainingExamples(ch, context.TrainingSet, out int weightSetCount);

Microsoft.ML.Vision (2)

ImageClassificationTrainer.cs (2)

664InitializeTrainingGraph(trainContext.TrainingSet.Data); 696CacheFeaturizedImagesToDisk(trainContext.TrainingSet.Data, _options.LabelColumnName,