Uses of Class
org.apache.ignite.ml.composition.stacking.SimpleStackedDatasetTrainer

Packages that use SimpleStackedDatasetTrainer

Package	Description
org.apache.ignite.ml.composition.stacking	Contains classes used for training with stacking technique.

Uses of SimpleStackedDatasetTrainer in org.apache.ignite.ml.composition.stacking

Subclasses of SimpleStackedDatasetTrainer in org.apache.ignite.ml.composition.stacking

Modifier and Type	Class and Description
class	StackedVectorDatasetTrainer<O,AM extends IgniteModel<Vector,O>,L> StackedDatasetTrainer with Vector as submodels input and output.

Methods in org.apache.ignite.ml.composition.stacking that return SimpleStackedDatasetTrainer

Modifier and Type	Method and Description
<M1 extends IgniteModel<I,I>> SimpleStackedDatasetTrainer<I,O,AM,L>	SimpleStackedDatasetTrainer.addTrainer(DatasetTrainer<M1,L> trainer) Adds submodel trainer along with converters needed on training and inference stages.
SimpleStackedDatasetTrainer<I,O,AM,L>	SimpleStackedDatasetTrainer.withAggregatorInputMerger(IgniteBinaryOperator<I> merger) Specify binary operator used to merge submodels outputs to one.
SimpleStackedDatasetTrainer<I,O,AM,L>	SimpleStackedDatasetTrainer.withAggregatorTrainer(DatasetTrainer<AM,L> aggregatorTrainer) Specify aggregator trainer.
<L1> SimpleStackedDatasetTrainer<I,O,AM,L1>	SimpleStackedDatasetTrainer.withConvertedLabels(IgniteFunction<L1,L> new2Old) Creates DatasetTrainer with same training logic, but able to accept labels of given new type of labels.
SimpleStackedDatasetTrainer<I,O,AM,L>	SimpleStackedDatasetTrainer.withEnvironmentBuilder(LearningEnvironmentBuilder envBuilder) Changes learning Environment.
SimpleStackedDatasetTrainer<I,O,AM,L>	SimpleStackedDatasetTrainer.withOriginalFeaturesDropped() Drop original features during training and inference.
SimpleStackedDatasetTrainer<I,O,AM,L>	SimpleStackedDatasetTrainer.withOriginalFeaturesKept() Keep original features using IgniteFunction.identity() as submodelInput2AggregatingInputConverter.
SimpleStackedDatasetTrainer<I,O,AM,L>	SimpleStackedDatasetTrainer.withOriginalFeaturesKept(IgniteFunction<I,I> submodelInput2AggregatingInputConverter) Keep original features during training and propagate submodels input to aggregator during inference using given function.