ActiveLearningConfig class final
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.
Constructors
- ActiveLearningConfig({int? maxDataItemCount, int? maxDataItemPercentage, SampleConfig? sampleConfig, TrainingConfig? trainingConfig})
- ActiveLearningConfig.fromJson(Object? j)
-
factory
Properties
- hashCode → int
-
The hash code for this object.
no setterinherited
- maxDataItemCount → int?
-
Max number of human labeled DataItems.
final
- maxDataItemPercentage → int?
-
Max percent of total DataItems for human labeling.
final
- qualifiedName → String
-
The fully qualified name of this message, i.e.,
google.protobuf.Durationorgoogle.rpc.ErrorInfo.finalinherited - runtimeType → Type
-
A representation of the runtime type of the object.
no setterinherited
- sampleConfig → SampleConfig?
-
Active learning data sampling config. For every active learning labeling
iteration, it will select a batch of data based on the sampling strategy.
final
- trainingConfig → 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.
final
Methods
-
noSuchMethod(
Invocation invocation) → dynamic -
Invoked when a nonexistent method or property is accessed.
inherited
-
toJson(
) → Object -
toString(
) → String -
A string representation of this object.
override
Operators
-
operator ==(
Object other) → bool -
The equality operator.
inherited
Constants
- fullyQualifiedName → const String