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