1 write to Host
Microsoft.ML.Data (1)
Evaluators\EvaluatorBase.cs (1)
251Host = env.Register("Aggregator");
73 references to Host
Microsoft.ML.Data (73)
Evaluators\AnomalyDetectionEvaluator.cs (10)
452Host.Assert(topK > 0); 453Host.Assert(nameIndex == -1 || nameIndex >= 0); 454Host.Assert(k > 0); 466_aucAggregator = new UnweightedAucAggregator(Host.Rand, reservoirSize); 480Host.Assert(!_streaming && PassNum < 2 || PassNum < 1); 504Host.Assert(!_streaming && PassNum < 2 || PassNum < 1); 505Host.Assert(schema.Label.HasValue); 511Host.AssertValue(_labelGetter); 512Host.AssertValue(_scoreGetter); 516Host.Assert(_topExamples.Count == 0);
Evaluators\BinaryClassifierEvaluator.cs (25)
574Host.Assert(Utils.Size(classNames) == 2); 575Host.Assert(aucReservoirSize >= -1); 576Host.Assert(prCount >= 0); 577Host.Assert(auPrcReservoirSize >= 0); 578Host.Assert(useRaw || 0 <= threshold && threshold <= 1); 586_aucAggregator = new WeightedAucAggregator(Host.Rand, aucReservoirSize); 588AuPrcAggregator = new WeightedAuPrcAggregator(Host.Rand, auPrcReservoirSize); 592_aucAggregator = new UnweightedAucAggregator(Host.Rand, aucReservoirSize); 594AuPrcAggregator = new UnweightedAuPrcAggregator(Host.Rand, auPrcReservoirSize); 606_prCurveReservoir = new ReservoirSamplerWithoutReplacement<RocInfo>(Host.Rand, prCount, prSampleGetter); 622Host.Assert(schema.Label.HasValue); 623Host.Assert(PassNum < 1); 629Host.AssertValue(_labelGetter); 630Host.AssertValue(_scoreGetter); 633Host.Assert(prob == null || prob.Count == 1); 640Host.Assert((schema.Weight != null) == Weighted); 679Host.Assert((_weightGetter != null) == Weighted); 719Host.AssertValue(_prCurveReservoir); 720Host.AssertValue(Scores); 721Host.AssertValue(Precision); 722Host.AssertValue(Recall); 723Host.AssertValue(FalsePositiveRate); 733Host.AssertValue(WeightedPrecision); 734Host.AssertValue(WeightedRecall); 735Host.AssertValue(WeightedFalsePositiveRate);
Evaluators\ClusteringEvaluator.cs (17)
410Host.Assert(features.HasValue); 430throw Host.Except("Invalid label: {0}", label); 433Host.Check(_scores.Length == _scoresArr.Length); 473Host.Check(_scores.Length == _scoresArr.Length); 491Host.AssertValue(row); 492Host.AssertValue(schema); 496Host.Assert(schema.Feature.HasValue); 500Host.Assert(score.Type.GetVectorSize() == _scoresArr.Length); 514Host.Assert(PassNum == 1 && _calculateDbi); 543Host.Assert(IsActive()); 548Host.AssertValue(_labelGetter); 549Host.AssertValue(_scoreGetter); 550Host.AssertValueOrNull(_weightGetter); 551Host.Assert(!_calculateDbi || _featGetter != null); 555Host.Assert(PassNum == 1 && _calculateDbi); 556Host.AssertValue(_featGetter); 557Host.AssertValue(_scoreGetter);
Evaluators\EvaluatorBase.cs (3)
252Host.AssertValueOrNull(stratName); 260Host.Check(PassNum == -1, "Start() should only be called before processing any data."); 296Host.Assert(PassNum < 1);
Evaluators\MulticlassClassificationEvaluator.cs (9)
400Host.Assert(outputTopKAcc == null || outputTopKAcc > 0); 401Host.Assert(scoreVectorSize > 0); 402Host.Assert(Utils.Size(classNames) == scoreVectorSize); 414Host.Assert(PassNum < 1); 415Host.Assert(schema.Label.HasValue); 418Host.Assert(score.Type.GetVectorSize() == _scoresArr.Length); 421Host.AssertValue(_labelGetter); 422Host.AssertValue(_scoreGetter); 445Host.Check(_scores.Length == _scoresArr.Length);
Evaluators\MultiOutputRegressionEvaluator.cs (2)
291Host.AssertValue(lossFunction); 292Host.Assert(size > 0);
Evaluators\QuantileRegressionEvaluator.cs (3)
223Host.Assert(size > 0); 224Host.Assert(slotNames.Length == 0 || slotNames.Length == size); 247Host.AssertValue(dvBldr);
Evaluators\RankingEvaluator.cs (2)
439Host.AssertValue(labelGains); 440Host.Assert(truncationLevel > 0);
Evaluators\RegressionEvaluator.cs (1)
162Host.AssertValue(dvBldr);
Evaluators\RegressionEvaluatorBase.cs (1)
195Host.AssertValue(lossFunction);