SsaSpikeDetector Class

Definition

Namespace:

Microsoft.ML.Transforms.TimeSeries

Assembly:

Microsoft.ML.TimeSeries.dll

Package:

Microsoft.ML.TimeSeries v3.0.1

ITransformer resulting from fitting a SsaSpikeEstimator.

public sealed class SsaSpikeDetector : Microsoft.ML.Transforms.TimeSeries.SsaAnomalyDetectionBaseWrapper, Microsoft.ML.ITransformer

type SsaSpikeDetector = class
    inherit SsaAnomalyDetectionBaseWrapper
    interface ITransformer
    interface ICanSaveModel

Public NotInheritable Class SsaSpikeDetector
Inherits SsaAnomalyDetectionBaseWrapper
Implements ITransformer

Inheritance

Object

SsaAnomalyDetectionBaseWrapper

SsaSpikeDetector

Implements

ICanSaveModel ITransformer

Methods

GetOutputSchema(DataViewSchema)	Schema propagation for transformers. Returns the output schema of the data, if the input schema is like the one provided. (Inherited from SsaAnomalyDetectionBaseWrapper)
GetStatefulRowToRowMapper(DataViewSchema)	Same as GetRowToRowMapper(DataViewSchema) but also supports mechanism to save the state. (Inherited from SsaAnomalyDetectionBaseWrapper)
Transform(IDataView)	Take the data in, make transformations, output the data. Note that IDataView's are lazy, so no actual transformations happen here, just schema validation. (Inherited from SsaAnomalyDetectionBaseWrapper)

Explicit Interface Implementations

ICanSaveModel.Save(ModelSaveContext)	For saving a model into a repository. (Inherited from SsaAnomalyDetectionBaseWrapper)
ITransformer.GetRowToRowMapper(DataViewSchema)	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 SsaAnomalyDetectionBaseWrapper)
ITransformer.IsRowToRowMapper	Whether a call to GetRowToRowMapper(DataViewSchema) should succeed, on an appropriate schema. (Inherited from SsaAnomalyDetectionBaseWrapper)

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, PredictionEngineOptions)	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.
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.