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-
(::Integer) — Max number of human labeled DataItems.
Note: The following fields are mutually exclusive:
max_data_item_count,max_data_item_percentage. If a field in that set is populated, all other fields in the set will automatically be cleared.
#max_data_item_count=
def max_data_item_count=(value) -> ::Integer-
value (::Integer) — Max number of human labeled DataItems.
Note: The following fields are mutually exclusive:
max_data_item_count,max_data_item_percentage. If a field in that set is populated, all other fields in the set will automatically be cleared.
-
(::Integer) — Max number of human labeled DataItems.
Note: The following fields are mutually exclusive:
max_data_item_count,max_data_item_percentage. If a field in that set is populated, all other fields in the set will automatically be cleared.
#max_data_item_percentage
def max_data_item_percentage() -> ::Integer-
(::Integer) — Max percent of total DataItems for human labeling.
Note: The following fields are mutually exclusive:
max_data_item_percentage,max_data_item_count. If a field in that set is populated, all other fields in the set will automatically be cleared.
#max_data_item_percentage=
def max_data_item_percentage=(value) -> ::Integer-
value (::Integer) — Max percent of total DataItems for human labeling.
Note: The following fields are mutually exclusive:
max_data_item_percentage,max_data_item_count. If a field in that set is populated, all other fields in the set will automatically be cleared.
-
(::Integer) — Max percent of total DataItems for human labeling.
Note: The following fields are mutually exclusive:
max_data_item_percentage,max_data_item_count. If a field in that set is populated, all other fields in the set will automatically be cleared.
#sample_config
def sample_config() -> ::Google::Cloud::AIPlatform::V1::SampleConfig- (::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- 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.
- (::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- (::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- 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.
- (::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.