1 write to TrainSet
Microsoft.ML.FastTree (1)
FastTree.cs (1)
194
TrainSet
= instanceConverter.FindBinsAndReturnDataset(trainData, PredictionKind, ParallelTraining, CategoricalFeatures, FastTreeTrainerOptions.CategoricalSplit);
50 references to TrainSet
Microsoft.ML.FastTree (50)
BoostingFastTree.cs (4)
66
TrainSet
, FastTreeTrainerOptions.NumberOfLeaves, FastTreeTrainerOptions.MinimumExampleCountPerLeaf, FastTreeTrainerOptions.EntropyCoefficient,
84
optimizationAlgorithm = new GradientDescent(Ensemble,
TrainSet
, InitTrainScores, gradientWrapper);
87
optimizationAlgorithm = new AcceleratedGradientDescent(Ensemble,
TrainSet
, InitTrainScores, gradientWrapper);
90
optimizationAlgorithm = new ConjugateGradientDescent(Ensemble,
TrainSet
, InitTrainScores, gradientWrapper);
FastTree.cs (10)
72
/// In the training process, <see cref="
TrainSet
"/>, <see cref="ValidSet"/>, <see cref="TestSets"/> would be
412
var activeFeatures = Utils.CreateArray(
TrainSet
.NumFeatures, true);
418
for (int i = 0; i <
TrainSet
.NumFeatures; ++i)
439
ch.Trace("Training {0}", GetDatasetStatistics(
TrainSet
));
465
return
TrainSet
.SampleWeights != null;
586
return new BaggingProvider(
TrainSet
, FastTreeTrainerOptions.NumberOfLeaves, FastTreeTrainerOptions.Seed, FastTreeTrainerOptions.BaggingExampleFraction);
762
Ensemble.PopulateRawThresholds(
TrainSet
);
827
if (set ==
TrainSet
)
828
st = OptimizationAlgorithm.GetScoreTracker("train",
TrainSet
, InitTrainScores);
877
if (set ==
TrainSet
)
FastTreeClassification.cs (5)
219
TrainSet
,
253
_trainSetLabels = GetClassificationLabelsFromRatings(
TrainSet
).ToArray(
TrainSet
.NumDocs);
259
return new BinaryClassificationTest(ConstructScoreTracker(
TrainSet
), _trainSetLabels, _sigmoidParameter);
265
TrainTest = new BinaryClassificationTest(ConstructScoreTracker(
TrainSet
), _trainSetLabels, _sigmoidParameter);
FastTreeRanking.cs (11)
201
_ensembleCompressor.Initialize(FastTreeTrainerOptions.NumberOfTrees,
TrainSet
,
TrainSet
.Ratings, FastTreeTrainerOptions.Seed);
207
return new LambdaRankObjectiveFunction(
TrainSet
,
TrainSet
.Ratings, FastTreeTrainerOptions, ParallelTraining);
215
_specialTrainSetTest = new FastNdcgTest(optimizationAlgorithm.TrainingScores,
TrainSet
.Ratings, FastTreeTrainerOptions.SortingAlgorithm, FastTreeTrainerOptions.EarlyStoppingMetrics);
224
return new RankingBaggingProvider(
TrainSet
, FastTreeTrainerOptions.NumberOfLeaves, FastTreeTrainerOptions.Seed, FastTreeTrainerOptions.BaggingExampleFraction);
233
return new NdcgTest(ConstructScoreTracker(
TrainSet
),
TrainSet
.Ratings, FastTreeTrainerOptions.SortingAlgorithm);
282
Tests.Add(CreateStandardTest(
TrainSet
));
399
double[] trainOutputs = Ensemble.GetTreeAt(Ensemble.NumTrees - 1).GetOutputs(
TrainSet
);
429
TrainSet
.Ratings,
FastTreeRegression.cs (5)
148
return new ObjectiveImpl(
TrainSet
, FastTreeTrainerOptions);
188
return new RegressionTest(ConstructScoreTracker(
TrainSet
));
212
Tests.Add(new RegressionTest(ConstructScoreTracker(
TrainSet
)));
276
Test trainRegressionTest = new RegressionTest(ConstructScoreTracker(
TrainSet
));
284
TrainTest = new RegressionTest(ConstructScoreTracker(
TrainSet
), FastTreeTrainerOptions.EarlyStoppingMetrics);
FastTreeTweedie.cs (5)
160
return new ObjectiveImpl(
TrainSet
, FastTreeTrainerOptions);
202
return new RegressionTest(ConstructScoreTracker(
TrainSet
));
218
Tests.Add(new RegressionTest(ConstructScoreTracker(
TrainSet
)));
255
Test trainRegressionTest = new RegressionTest(ConstructScoreTracker(
TrainSet
));
263
TrainTest = new RegressionTest(ConstructScoreTracker(
TrainSet
), FastTreeTrainerOptions.EarlyStoppingMetrics);
RandomForest.cs (2)
46
var optimizationAlgorithm = new RandomForestOptimizer(Ensemble,
TrainSet
, InitTrainScores, gradientWrapper);
66
TrainSet
, FastTreeTrainerOptions.NumberOfLeaves, FastTreeTrainerOptions.MinimumExampleCountPerLeaf, FastTreeTrainerOptions.EntropyCoefficient,
RandomForestClassification.cs (5)
343
newTree.PopulateThresholds(
TrainSet
);
350
return new ObjectiveFunctionImpl(
TrainSet
, _trainSetLabels, FastTreeTrainerOptions);
357
_trainSetLabels =
TrainSet
.Ratings.Select(x => x >= 1).ToArray(
TrainSet
.NumDocs);
362
return new BinaryClassificationTest(ConstructScoreTracker(
TrainSet
), _trainSetLabels, 1);
RandomForestRegression.cs (3)
475
newTree.PopulateThresholds(
TrainSet
);
486
return ObjectiveFunctionImplBase.Create(
TrainSet
, FastTreeTrainerOptions);
491
return new RegressionTest(ConstructScoreTracker(
TrainSet
));