Vertex AI V1 API - Class Google::Cloud::AIPlatform::V1::ActiveLearningConfig (v0.21.0)

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Reference documentation and code samples for the Vertex AI V1 API class Google::Cloud::AIPlatform::V1::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.

Inherits

• Object

Extended By

• Google::Protobuf::MessageExts::ClassMethods

Includes

• Google::Protobuf::MessageExts

Methods

#max_data_item_count

def max_data_item_count() -> ::Integer

Returns

• (::Integer) — Max number of human labeled DataItems.

#max_data_item_count=

def max_data_item_count=(value) -> ::Integer

Parameter

• value (::Integer) — Max number of human labeled DataItems.

Returns

• (::Integer) — Max number of human labeled DataItems.

#max_data_item_percentage

def max_data_item_percentage() -> ::Integer

Returns

• (::Integer) — Max percent of total DataItems for human labeling.

#max_data_item_percentage=

def max_data_item_percentage=(value) -> ::Integer

Parameter

• value (::Integer) — Max percent of total DataItems for human labeling.

Returns

• (::Integer) — Max percent of total DataItems for human labeling.

#sample_config

def sample_config() -> ::Google::Cloud::AIPlatform::V1::SampleConfig

Returns

• (::Google::Cloud::AIPlatform::V1::SampleConfig) — Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.

#sample_config=

def sample_config=(value) -> ::Google::Cloud::AIPlatform::V1::SampleConfig

Parameter

• value (::Google::Cloud::AIPlatform::V1::SampleConfig) — Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.

Returns

• (::Google::Cloud::AIPlatform::V1::SampleConfig) — Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.

#training_config

def training_config() -> ::Google::Cloud::AIPlatform::V1::TrainingConfig

Returns

• (::Google::Cloud::AIPlatform::V1::TrainingConfig) — 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.

#training_config=

def training_config=(value) -> ::Google::Cloud::AIPlatform::V1::TrainingConfig

Parameter

• value (::Google::Cloud::AIPlatform::V1::TrainingConfig) — 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.

Returns

• (::Google::Cloud::AIPlatform::V1::TrainingConfig) — 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.