IidAnomalyDetectionBaseWrapper Class

Definition

Namespace:

Microsoft.ML.Transforms.TimeSeries

Assembly:

Microsoft.ML.TimeSeries.dll

Package:

Microsoft.ML.TimeSeries v3.0.1

The is the wrapper to Microsoft.ML.Transforms.TimeSeries.IidAnomalyDetectionBaseWrapper.IidAnomalyDetectionBase that computes the p-values and martingale scores for a supposedly i.i.d input sequence of floats. In other words, it assumes the input sequence represents the raw anomaly score which might have been computed via another process.

public class IidAnomalyDetectionBaseWrapper : Microsoft.ML.ITransformer

type IidAnomalyDetectionBaseWrapper = class
    interface ITransformer
    interface ICanSaveModel

Public Class IidAnomalyDetectionBaseWrapper
Implements ITransformer

Inheritance

Object

IidAnomalyDetectionBaseWrapper

Derived

Microsoft.ML.Transforms.TimeSeries.IidChangePointDetector

Microsoft.ML.Transforms.TimeSeries.IidSpikeDetector

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.
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, 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.