Class GoogleCloudAiplatformV1SchemaTrainingjobDefinitionWindowConfig

Config that contains the strategy used to generate sliding windows in time series training. A window is a series of rows that comprise the context up to the time of prediction, and the horizon following. The corresponding row for each window marks the start of the forecast horizon. Each window is used as an input example for training/evaluation.

Inheritance

object

GoogleCloudAiplatformV1SchemaTrainingjobDefinitionWindowConfig

Implements

IDirectResponseSchema

Inherited Members

object.Equals(object)

object.Equals(object, object)

object.GetHashCode()

object.GetType()

object.MemberwiseClone()

object.ReferenceEquals(object, object)

object.ToString()

Namespace: Google.Apis.Aiplatform.v1.Data

Assembly: Google.Apis.Aiplatform.v1.dll

Syntax

public class GoogleCloudAiplatformV1SchemaTrainingjobDefinitionWindowConfig : IDirectResponseSchema

Properties

Column

Name of the column that should be used to generate sliding windows. The column should contain either booleans or string booleans; if the value of the row is True, generate a sliding window with the horizon starting at that row. The column will not be used as a feature in training.

Declaration

[JsonProperty("column")]
public virtual string Column { get; set; }

Property Value

Type	Description
string

ETag

The ETag of the item.

Declaration

public virtual string ETag { get; set; }

Property Value

Type	Description
string

MaxCount

Maximum number of windows that should be generated across all time series.

Declaration

[JsonProperty("maxCount")]
public virtual long? MaxCount { get; set; }

Property Value

Type	Description
long?

StrideLength

Stride length used to generate input examples. Within one time series, every {$STRIDE_LENGTH} rows will be used to generate a sliding window.

Declaration

[JsonProperty("strideLength")]
public virtual long? StrideLength { get; set; }

Property Value

Type	Description
long?

Implements

IDirectResponseSchema