1 write to AnomalyDetection
Microsoft.ML.Data (1)
MLContext.cs (1)
155AnomalyDetection = new AnomalyDetectionCatalog(_env);
29 references to AnomalyDetection
Microsoft.ML.IntegrationTests (2)
Evaluation.cs (2)
38var pipeline = mlContext.AnomalyDetection.Trainers.RandomizedPca(); 46var metrics = mlContext.AnomalyDetection.Evaluate(scoredTest);
Microsoft.ML.Samples (6)
Dynamic\Trainers\AnomalyDetection\RandomizedPcaSample.cs (1)
36var pipeline = mlContext.AnomalyDetection.Trainers.RandomizedPca(
Dynamic\Trainers\AnomalyDetection\RandomizedPcaSampleWithOptions.cs (1)
45var pipeline = mlContext.AnomalyDetection.Trainers.RandomizedPca(
Dynamic\Transforms\TimeSeries\DetectEntireAnomalyBySrCnn.cs (1)
38var outputDataView = ml.AnomalyDetection.DetectEntireAnomalyBySrCnn(dataView, outputColumnName, inputColumnName,
Dynamic\Transforms\TimeSeries\DetectSeasonality.cs (1)
31int period = mlContext.AnomalyDetection.DetectSeasonality(
Dynamic\Transforms\TimeSeries\LocalizeRootCause.cs (1)
23RootCause prediction = mlContext.AnomalyDetection.LocalizeRootCause(data);
Dynamic\Transforms\TimeSeries\LocalizeRootCauseMultidimension.cs (1)
24List<RootCause> prediction = mlContext.AnomalyDetection.LocalizeRootCauses(data);
Microsoft.ML.Tests (9)
AnomalyDetectionTests.cs (9)
34var metrics = ML.AnomalyDetection.Evaluate(transformedData, falsePositiveCount: 5); 50Assert.Throws<ArgumentOutOfRangeException>(() => ML.AnomalyDetection.Evaluate(transformedData)); 62var trainer1 = mlContext.AnomalyDetection.Trainers.RandomizedPca(featureColumnName: nameof(DataPoint.Features), rank: 1, ensureZeroMean: false); 77var trainer2 = mlContext.AnomalyDetection.Trainers.RandomizedPca(options); 92var trainer1 = mlContext.AnomalyDetection.Trainers.RandomizedPca(featureColumnName: nameof(DataPoint.Features), rank: 1, ensureZeroMean: false); 107var trainer2 = mlContext.AnomalyDetection.Trainers.RandomizedPca(options); 200var transformer = mlContext.AnomalyDetection.ChangeModelThreshold(model, 0.3f); 249var trainer = ML.AnomalyDetection.Trainers.RandomizedPca(); 264var trainer = mlContext.AnomalyDetection.Trainers.RandomizedPca(
Microsoft.ML.TimeSeries.Tests (12)
TimeSeriesDirectApi.cs (12)
623var outputDataView = ml.AnomalyDetection.DetectEntireAnomalyBySrCnn(dataView, outputColumnName, inputColumnName, 703var outputDataView = ml.AnomalyDetection.DetectEntireAnomalyBySrCnn(dataView, outputColumnName, inputColumnName, options); 750var outputDataView = ml.AnomalyDetection.DetectEntireAnomalyBySrCnn(dataView, outputColumnName, inputColumnName, options); 805var outputDataView = ml.AnomalyDetection.DetectEntireAnomalyBySrCnn(dataView, outputColumnName, inputColumnName, options); 864var outputDataView = ml.AnomalyDetection.DetectEntireAnomalyBySrCnn(dataView, outputColumnName, inputColumnName, options); 932var outputDataView = ml.AnomalyDetection.DetectEntireAnomalyBySrCnn(dataView, outputColumnName, inputColumnName, options); 961RootCause rootCause = ml.AnomalyDetection.LocalizeRootCause(rootCauseLocalizationInput); 988List<RootCause> preparedCauses = ml.AnomalyDetection.LocalizeRootCauses(rootCauseLocalizationInput); 1038RootCause rootCause = ml.AnomalyDetection.LocalizeRootCause(rootCauseLocalizationInput); 1079int period = mlContext.AnomalyDetection.DetectSeasonality(dataView, nameof(TimeSeriesDataDouble.Value), seasonalityWindowSize); 1188RootCause rootCause = ml.AnomalyDetection.LocalizeRootCause(rootCauseLocalizationInput); 1222RootCause rootCause = ml.AnomalyDetection.LocalizeRootCause(rootCauseLocalizationInput);