public sealed class ActiveLearningConfig : IMessage<ActiveLearningConfig>, IEquatable<ActiveLearningConfig>, IDeepCloneable<ActiveLearningConfig>, IBufferMessage, IMessage
Reference documentation and code samples for the Vertex AI v1beta1 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.
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.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-28 UTC."],[[["\u003cp\u003e\u003ccode\u003eActiveLearningConfig\u003c/code\u003e is a class within the Vertex AI v1beta1 API, used to configure parameters for the active learning pipeline.\u003c/p\u003e\n"],["\u003cp\u003eThis class, \u003ccode\u003eActiveLearningConfig\u003c/code\u003e, is designed for labeling data incrementally over multiple iterations, selecting data batches based on a sampling strategy.\u003c/p\u003e\n"],["\u003cp\u003eThe \u003ccode\u003eActiveLearningConfig\u003c/code\u003e class includes properties such as \u003ccode\u003eMaxDataItemCount\u003c/code\u003e, \u003ccode\u003eMaxDataItemPercentage\u003c/code\u003e, \u003ccode\u003eSampleConfig\u003c/code\u003e, and \u003ccode\u003eTrainingConfig\u003c/code\u003e, all of which enable configuration for active learning tasks.\u003c/p\u003e\n"],["\u003cp\u003eIt inherits from the base \u003ccode\u003eobject\u003c/code\u003e class and implements interfaces like \u003ccode\u003eIMessage\u003c/code\u003e, \u003ccode\u003eIEquatable\u003c/code\u003e, \u003ccode\u003eIDeepCloneable\u003c/code\u003e, and \u003ccode\u003eIBufferMessage\u003c/code\u003e, supporting various functionalities related to data handling.\u003c/p\u003e\n"],["\u003cp\u003eThe latest version available is \u003ccode\u003e1.0.0-beta21\u003c/code\u003e, and previous versions such as \u003ccode\u003e1.0.0-beta20\u003c/code\u003e are also available for reference.\u003c/p\u003e\n"]]],[],null,["# Vertex AI v1beta1 API - Class ActiveLearningConfig (1.0.0-beta47)\n\nVersion latestkeyboard_arrow_down\n\n- [1.0.0-beta47 (latest)](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1.ActiveLearningConfig)\n- [1.0.0-beta46](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/1.0.0-beta46/Google.Cloud.AIPlatform.V1Beta1.ActiveLearningConfig) \n\n public sealed class ActiveLearningConfig : IMessage\u003cActiveLearningConfig\u003e, IEquatable\u003cActiveLearningConfig\u003e, IDeepCloneable\u003cActiveLearningConfig\u003e, IBufferMessage, IMessage\n\nReference documentation and code samples for the Vertex AI v1beta1 API class ActiveLearningConfig.\n\nParameters that configure the active learning pipeline. Active learning will\nlabel the data incrementally by several iterations. For every iteration, it\nwill select a batch of data based on the sampling strategy. \n\nInheritance\n-----------\n\n[object](https://learn.microsoft.com/dotnet/api/system.object) \\\u003e ActiveLearningConfig \n\nImplements\n----------\n\n[IMessage](https://cloud.google.com/dotnet/docs/reference/Google.Protobuf/latest/Google.Protobuf.IMessage-1.html)[ActiveLearningConfig](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1.ActiveLearningConfig), [IEquatable](https://learn.microsoft.com/dotnet/api/system.iequatable-1)[ActiveLearningConfig](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1.ActiveLearningConfig), [IDeepCloneable](https://cloud.google.com/dotnet/docs/reference/Google.Protobuf/latest/Google.Protobuf.IDeepCloneable-1.html)[ActiveLearningConfig](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1.ActiveLearningConfig), [IBufferMessage](https://cloud.google.com/dotnet/docs/reference/Google.Protobuf/latest/Google.Protobuf.IBufferMessage.html), [IMessage](https://cloud.google.com/dotnet/docs/reference/Google.Protobuf/latest/Google.Protobuf.IMessage.html) \n\nInherited Members\n-----------------\n\n[object.GetHashCode()](https://learn.microsoft.com/dotnet/api/system.object.gethashcode) \n[object.GetType()](https://learn.microsoft.com/dotnet/api/system.object.gettype) \n[object.ToString()](https://learn.microsoft.com/dotnet/api/system.object.tostring)\n\nNamespace\n---------\n\n[Google.Cloud.AIPlatform.V1Beta1](/dotnet/docs/reference/Google.Cloud.AIPlatform.V1Beta1/latest/Google.Cloud.AIPlatform.V1Beta1)\n\nAssembly\n--------\n\nGoogle.Cloud.AIPlatform.V1Beta1.dll\n\nConstructors\n------------\n\n### ActiveLearningConfig()\n\n public ActiveLearningConfig()\n\n### ActiveLearningConfig(ActiveLearningConfig)\n\n public ActiveLearningConfig(ActiveLearningConfig other)\n\nProperties\n----------\n\n### HasMaxDataItemCount\n\n public bool HasMaxDataItemCount { get; }\n\nGets whether the \"max_data_item_count\" field is set\n\n### HasMaxDataItemPercentage\n\n public bool HasMaxDataItemPercentage { get; }\n\nGets whether the \"max_data_item_percentage\" field is set\n\n### HumanLabelingBudgetCase\n\n public ActiveLearningConfig.HumanLabelingBudgetOneofCase HumanLabelingBudgetCase { get; }\n\n### MaxDataItemCount\n\n public long MaxDataItemCount { get; set; }\n\nMax number of human labeled DataItems.\n\n### MaxDataItemPercentage\n\n public int MaxDataItemPercentage { get; set; }\n\nMax percent of total DataItems for human labeling.\n\n### SampleConfig\n\n public SampleConfig SampleConfig { get; set; }\n\nActive learning data sampling config. For every active learning labeling\niteration, it will select a batch of data based on the sampling strategy.\n\n### TrainingConfig\n\n public TrainingConfig TrainingConfig { get; set; }\n\nCMLE training config. For every active learning labeling iteration, system\nwill train a machine learning model on CMLE. The trained model will be used\nby data sampling algorithm to select DataItems."]]
