Uses of Interface
org.apache.ignite.ml.math.functions.IgniteBinaryOperator

Packages that use IgniteBinaryOperator

Package	Description
org.apache.ignite.ml.composition.stacking	Contains classes used for training with stacking technique.
org.apache.ignite.ml.dataset	Base package for machine learning dataset classes.
org.apache.ignite.ml.dataset.impl.cache	Base package for cache based implementation of machine learning dataset.
org.apache.ignite.ml.dataset.impl.local	Base package for local implementation of machine learning dataset.
org.apache.ignite.ml.dataset.primitive	Package that contains basic primitives build on top of Dataset.

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

Methods in org.apache.ignite.ml.composition.stacking with parameters of type IgniteBinaryOperator

Modifier and Type	Method and Description
SimpleStackedDatasetTrainer<I,O,AM,L>	SimpleStackedDatasetTrainer.withAggregatorInputMerger(IgniteBinaryOperator<I> merger) Specify binary operator used to merge submodels outputs to one.
StackedDatasetTrainer<IS,IA,O,AM,L>	StackedDatasetTrainer.withAggregatorInputMerger(IgniteBinaryOperator<IA> merger) Specify binary operator used to merge submodels outputs to one.
StackedVectorDatasetTrainer<O,AM,L>	StackedVectorDatasetTrainer.withAggregatorInputMerger(IgniteBinaryOperator<Vector> merger) Specify binary operator used to merge submodels outputs to one.

Constructors in org.apache.ignite.ml.composition.stacking with parameters of type IgniteBinaryOperator

Constructor and Description
SimpleStackedDatasetTrainer(DatasetTrainer<AM,L> aggregatingTrainer, IgniteBinaryOperator<I> aggregatingInputMerger) Construct instance of this class.
SimpleStackedDatasetTrainer(DatasetTrainer<AM,L> aggregatingTrainer, IgniteBinaryOperator<I> aggregatingInputMerger, IgniteFunction<I,I> submodelInput2AggregatingInputConverter, IgniteFunction<Vector,I> vector2SubmodelInputConverter, IgniteFunction<I,Vector> submodelOutput2VectorConverter) Construct instance of this class.
StackedDatasetTrainer(DatasetTrainer<AM,L> aggregatorTrainer, IgniteBinaryOperator<IA> aggregatingInputMerger, IgniteFunction<IS,IA> submodelInput2AggregatingInputConverter) Constructs instance of this class.
StackedDatasetTrainer(DatasetTrainer<AM,L> aggregatorTrainer, IgniteBinaryOperator<IA> aggregatingInputMerger, IgniteFunction<IS,IA> submodelInput2AggregatingInputConverter, List<DatasetTrainer<IgniteModel<IS,IA>,L>> submodelsTrainers, IgniteFunction<Vector,IS> vector2SubmodelInputConverter, IgniteFunction<IA,Vector> submodelOutput2VectorConverter) Create instance of this class.

Uses of IgniteBinaryOperator in org.apache.ignite.ml.dataset

Methods in org.apache.ignite.ml.dataset with parameters of type IgniteBinaryOperator

Modifier and Type	Method and Description
default <R> R	Dataset.compute(IgniteBiFunction<D,LearningEnvironment,R> map, IgniteBinaryOperator<R> reduce) Applies the specified map function to every partition data and LearningEnvironment in the dataset and then reduces map results to final result by using the reduce function.
<R> R	Dataset.compute(IgniteBiFunction<D,LearningEnvironment,R> map, IgniteBinaryOperator<R> reduce, R identity) Applies the specified map function to every partition data and LearningEnvironment in the dataset and then reduces map results to final result by using the reduce function.
default <R> R	Dataset.compute(IgniteFunction<D,R> map, IgniteBinaryOperator<R> reduce) Applies the specified map function to every partition data in the dataset and then reduces map results to final result by using the reduce function.
default <R> R	Dataset.compute(IgniteFunction<D,R> map, IgniteBinaryOperator<R> reduce, R identity) Applies the specified map function to every partition data in the dataset and then reduces map results to final result by using the reduce function.
default <R> R	Dataset.computeWithCtx(IgniteBiFunction<C,D,R> map, IgniteBinaryOperator<R> reduce) Applies the specified map function to every partition data and context in the dataset and then reduces map results to final result by using the reduce function.
default <R> R	Dataset.computeWithCtx(IgniteBiFunction<C,D,R> map, IgniteBinaryOperator<R> reduce, R identity) Applies the specified map function to every partition data and context in the dataset and then reduces map results to final result by using the reduce function.
default <R> R	Dataset.computeWithCtx(IgniteTriFunction<C,D,LearningEnvironment,R> map, IgniteBinaryOperator<R> reduce) Applies the specified map function to every partition data, context and LearningEnvironment in the dataset and then reduces map results to final result by using the reduce function.
<R> R	Dataset.computeWithCtx(IgniteTriFunction<C,D,LearningEnvironment,R> map, IgniteBinaryOperator<R> reduce, R identity) Applies the specified map function to every partition data, context and partition index in the dataset and then reduces map results to final result by using the reduce function.

Uses of IgniteBinaryOperator in org.apache.ignite.ml.dataset.impl.cache

Methods in org.apache.ignite.ml.dataset.impl.cache with parameters of type IgniteBinaryOperator

Modifier and Type	Method and Description
<R> R	CacheBasedDataset.compute(IgniteBiFunction<D,LearningEnvironment,R> map, IgniteBinaryOperator<R> reduce, R identity) Applies the specified map function to every partition data and LearningEnvironment in the dataset and then reduces map results to final result by using the reduce function.
<R> R	CacheBasedDataset.computeWithCtx(IgniteTriFunction<C,D,LearningEnvironment,R> map, IgniteBinaryOperator<R> reduce, R identity) Applies the specified map function to every partition data, context and partition index in the dataset and then reduces map results to final result by using the reduce function.

Uses of IgniteBinaryOperator in org.apache.ignite.ml.dataset.impl.local

Methods in org.apache.ignite.ml.dataset.impl.local with parameters of type IgniteBinaryOperator

Modifier and Type	Method and Description
<R> R	LocalDataset.compute(IgniteBiFunction<D,LearningEnvironment,R> map, IgniteBinaryOperator<R> reduce, R identity) Applies the specified map function to every partition data and LearningEnvironment in the dataset and then reduces map results to final result by using the reduce function.
<R> R	LocalDataset.computeWithCtx(IgniteTriFunction<C,D,LearningEnvironment,R> map, IgniteBinaryOperator<R> reduce, R identity) Applies the specified map function to every partition data, context and partition index in the dataset and then reduces map results to final result by using the reduce function.

Uses of IgniteBinaryOperator in org.apache.ignite.ml.dataset.primitive

Methods in org.apache.ignite.ml.dataset.primitive with parameters of type IgniteBinaryOperator

Modifier and Type	Method and Description
<R> R	DatasetWrapper.compute(IgniteBiFunction<D,LearningEnvironment,R> map, IgniteBinaryOperator<R> reduce, R identity) Applies the specified map function to every partition data and LearningEnvironment in the dataset and then reduces map results to final result by using the reduce function.
<R> R	DatasetWrapper.computeWithCtx(IgniteTriFunction<C,D,LearningEnvironment,R> map, IgniteBinaryOperator<R> reduce, R identity) Applies the specified map function to every partition data, context and partition index in the dataset and then reduces map results to final result by using the reduce function.