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

Packages that use StackedVectorDatasetTrainer

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

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

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

Modifier and Type	Method and Description
<M1 extends IgniteModel<Matrix,Matrix>> StackedVectorDatasetTrainer<O,AM,L>	StackedVectorDatasetTrainer.addMatrix2MatrixTrainer(DatasetTrainer<M1,L> trainer) Shortcut for adding trainer Matrix -> Matrix where this trainer is treated as Vector -> Vector, where input Vector is turned into 1 x cols Matrix and output is a first row of output Matrix.
<M1 extends IgniteModel<Vector,Vector>> StackedVectorDatasetTrainer<O,AM,L>	StackedVectorDatasetTrainer.addTrainer(DatasetTrainer<M1,L> trainer) Adds submodel trainer along with converters needed on training and inference stages.
<M1 extends IgniteModel<Vector,Double>> StackedVectorDatasetTrainer<O,AM,L>	StackedVectorDatasetTrainer.addTrainerWithDoubleOutput(DatasetTrainer<M1,L> trainer) Shortcut for adding trainer Vector -> Double where this trainer is treated as Vector -> Vector, where output Vector is constructed by wrapping double value.
StackedVectorDatasetTrainer<O,AM,L>	StackedVectorDatasetTrainer.withAggregatorInputMerger(IgniteBinaryOperator<Vector> merger) Specify binary operator used to merge submodels outputs to one.
StackedVectorDatasetTrainer<O,AM,L>	StackedVectorDatasetTrainer.withAggregatorTrainer(DatasetTrainer<AM,L> aggregatorTrainer) Specify aggregator trainer.
<L1> StackedVectorDatasetTrainer<O,AM,L1>	StackedVectorDatasetTrainer.withConvertedLabels(IgniteFunction<L1,L> new2Old) Creates DatasetTrainer with same training logic, but able to accept labels of given new type of labels.
StackedVectorDatasetTrainer<O,AM,L>	StackedVectorDatasetTrainer.withEnvironmentBuilder(LearningEnvironmentBuilder envBuilder) Changes learning Environment.
StackedVectorDatasetTrainer<O,AM,L>	StackedVectorDatasetTrainer.withOriginalFeaturesDropped() Drop original features during training and inference.
StackedVectorDatasetTrainer<O,AM,L>	StackedVectorDatasetTrainer.withOriginalFeaturesKept() Keep original features using IgniteFunction.identity() as submodelInput2AggregatingInputConverter.
StackedVectorDatasetTrainer<O,AM,L>	StackedVectorDatasetTrainer.withOriginalFeaturesKept(IgniteFunction<Vector,Vector> submodelInput2AggregatingInputConverter) Keep original features during training and propagate submodels input to aggregator during inference using given function.
StackedVectorDatasetTrainer<O,AM,L>	StackedVectorDatasetTrainer.withSubmodelOutput2VectorConverter(IgniteFunction<Vector,Vector> submodelOutput2VectorConverter) Set function used for conversion of submodel output to Vector.
StackedVectorDatasetTrainer<O,AM,L>	StackedVectorDatasetTrainer.withVector2SubmodelInputConverter(IgniteFunction<Vector,Vector> vector2SubmodelInputConverter) Set function used for conversion of Vector to submodel input.