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

Packages that use IgniteBinaryOperator

Package	Description
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.
org.apache.ignite.ml.math.distributed	Contains classes for distribution support.

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,Integer,R> map, IgniteBinaryOperator<R> reduce) Applies the specified map function to every partition data and partition index in the dataset and then reduces map results to final result by using the reduce function.
<R> R	Dataset.compute(IgniteBiFunction<D,Integer,R> map, IgniteBinaryOperator<R> reduce, R identity) Applies the specified map function to every partition data and partition index 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,Integer,R> map, IgniteBinaryOperator<R> reduce) 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.
<R> R	Dataset.computeWithCtx(IgniteTriFunction<C,D,Integer,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,Integer,R> map, IgniteBinaryOperator<R> reduce, R identity) Applies the specified map function to every partition data and partition index in the dataset and then reduces map results to final result by using the reduce function.
<R> R	CacheBasedDataset.computeWithCtx(IgniteTriFunction<C,D,Integer,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,Integer,R> map, IgniteBinaryOperator<R> reduce, R identity) Applies the specified map function to every partition data and partition index in the dataset and then reduces map results to final result by using the reduce function.
<R> R	LocalDataset.computeWithCtx(IgniteTriFunction<C,D,Integer,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,Integer,R> map, IgniteBinaryOperator<R> reduce, R identity) Applies the specified map function to every partition data and partition index in the dataset and then reduces map results to final result by using the reduce function.
<R> R	DatasetWrapper.computeWithCtx(IgniteTriFunction<C,D,Integer,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.math.distributed

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

Modifier and Type	Method and Description
static <K,V,A,W> A	CacheUtils.reduce(String cacheName, Ignite ignite, IgniteTriFunction<W,javax.cache.Cache.Entry<K,V>,A,A> acc, IgniteSupplier<W> supp, IgniteSupplier<Iterable<javax.cache.Cache.Entry<K,V>>> entriesGen, IgniteBinaryOperator<A> comb, IgniteSupplier<A> zeroValSupp) Distributed version of fold operation.
static <K,V,A,W> A	CacheUtils.reduce(String cacheName, IgniteTriFunction<W,javax.cache.Cache.Entry<K,V>,A,A> acc, IgniteSupplier<W> supp, IgniteSupplier<Iterable<javax.cache.Cache.Entry<K,V>>> entriesGen, IgniteBinaryOperator<A> comb, IgniteSupplier<A> zeroValSupp) Distributed version of fold operation.