SrCnnAnomalyDetector Class


ITransformer resulting from fitting a SrCnnAnomalyEstimator.

public sealed class SrCnnAnomalyDetector : Microsoft.ML.Transforms.TimeSeries.SrCnnAnomalyDetectionBase, Microsoft.ML.ITransformer
type SrCnnAnomalyDetector = class
    inherit SrCnnAnomalyDetectionBase
    interface ITransformer
    interface ICanSaveModel
Public NotInheritable Class SrCnnAnomalyDetector
Inherits SrCnnAnomalyDetectionBase
Implements ITransformer



Schema propagation for transformers. Returns the output schema of the data, if the input schema is like the one provided.

(Inherited from SrCnnAnomalyDetectionBase)

Same as GetRowToRowMapper(DataViewSchema) but also supports mechanism to save the state.

(Inherited from SrCnnAnomalyDetectionBase)

Initialize a transformer which will do lambda transfrom on input data in prediction engine. No actual transformations happen here, just schema validation.

(Inherited from SrCnnAnomalyDetectionBase)

Explicit Interface Implementations


For saving a model into a repository.

(Inherited from SrCnnAnomalyDetectionBase)

Constructs a row-to-row mapper based on an input schema. If IsRowToRowMapper is false, then an exception should be thrown. If the input schema is in any way unsuitable for constructing the mapper, an exception should likewise be thrown.

(Inherited from SrCnnAnomalyDetectionBase)

Whether a call to GetRowToRowMapper(DataViewSchema) should succeed, on an appropriate schema.

(Inherited from SrCnnAnomalyDetectionBase)

Extension Methods

Preview(ITransformer, IDataView, Int32)

Preview an effect of the transformer on a given data.

Append<TTrans>(ITransformer, TTrans)

Create a new transformer chain, by appending another transformer to the end of this transformer chain.

CreateTimeSeriesEngine<TSrc,TDst>(ITransformer, IHostEnvironment, Boolean, SchemaDefinition, SchemaDefinition)

TimeSeriesPredictionEngine<TSrc,TDst> creates a prediction engine for a time series pipeline. It updates the state of time series model with observations seen at prediction phase and allows checkpointing the model.

Applies to