Cloud AI Platform v1 API - Class ActiveLearningConfig (3.11.0)

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public sealed class ActiveLearningConfig : IMessage<ActiveLearningConfig>, IEquatable<ActiveLearningConfig>, IDeepCloneable<ActiveLearningConfig>, IBufferMessage, IMessage

Reference documentation and code samples for the Cloud AI Platform v1 API class ActiveLearningConfig.

Parameters that configure the active learning pipeline. Active learning will label the data incrementally by several iterations. For every iteration, it will select a batch of data based on the sampling strategy.

Inheritance

object > ActiveLearningConfig

Implements

IMessageActiveLearningConfig, IEquatableActiveLearningConfig, IDeepCloneableActiveLearningConfig, IBufferMessage, IMessage

Inherited Members

object.GetHashCode()

object.GetType()

object.ToString()

Namespace

Google.Cloud.AIPlatform.V1

Assembly

Google.Cloud.AIPlatform.V1.dll

Constructors

ActiveLearningConfig()

public ActiveLearningConfig()

ActiveLearningConfig(ActiveLearningConfig)

public ActiveLearningConfig(ActiveLearningConfig other)

Parameter
Name	Description
other	ActiveLearningConfig

Properties

HasMaxDataItemCount

public bool HasMaxDataItemCount { get; }

Gets whether the "max_data_item_count" field is set

Property Value
Type	Description
bool

HasMaxDataItemPercentage

public bool HasMaxDataItemPercentage { get; }

Gets whether the "max_data_item_percentage" field is set

Property Value
Type	Description
bool

HumanLabelingBudgetCase

public ActiveLearningConfig.HumanLabelingBudgetOneofCase HumanLabelingBudgetCase { get; }

Property Value
Type	Description
ActiveLearningConfigHumanLabelingBudgetOneofCase

MaxDataItemCount

public long MaxDataItemCount { get; set; }

Max number of human labeled DataItems.

Property Value
Type	Description
long

MaxDataItemPercentage

public int MaxDataItemPercentage { get; set; }

Max percent of total DataItems for human labeling.

Property Value
Type	Description
int

SampleConfig

public SampleConfig SampleConfig { get; set; }

Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.

Property Value
Type	Description
SampleConfig

TrainingConfig

public TrainingConfig TrainingConfig { get; set; }

CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.

Property Value
Type	Description
TrainingConfig