SsaAnomalyDetectionBaseWrapper Class

Definition

The wrapper to Microsoft.ML.Transforms.TimeSeries.SsaAnomalyDetectionBaseWrapper.SsaAnomalyDetectionBase that implements the general anomaly detection transform based on Singular Spectrum modeling of the time-series. For the details of the Singular Spectrum Analysis (SSA), refer to http://arxiv.org/pdf/1206.6910.pdf.

public class SsaAnomalyDetectionBaseWrapper : Microsoft.ML.ITransformer
type SsaAnomalyDetectionBaseWrapper = class
    interface ITransformer
    interface ICanSaveModel
Public Class SsaAnomalyDetectionBaseWrapper
Implements ITransformer
Inheritance
SsaAnomalyDetectionBaseWrapper
Derived
Implements

Methods

GetOutputSchema(DataViewSchema)

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

GetStatefulRowToRowMapper(DataViewSchema)

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

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.

Explicit Interface Implementations

ICanSaveModel.Save(ModelSaveContext)

For saving a model into a repository.

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.

ITransformer.IsRowToRowMapper

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

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