## Uses of Interface
org.apache.ignite.ml.math.functions.IgniteTriFunction

- Packages that use IgniteTriFunction
  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.functions | Contains serializable functions for distributed code algebra.
  org.apache.ignite.ml.math.primitives.matrix | Contains matrix related classes.
  org.apache.ignite.ml.math.primitives.matrix.impl | Contains several matrix implementations.
  org.apache.ignite.ml.math.primitives.matrix.storage | Contains several matrix storages.
  org.apache.ignite.ml.math.util | Some math utils.

- - ### Uses of IgniteTriFunction in org.apache.ignite.ml.dataset

    Methods in org.apache.ignite.ml.dataset with parameters of type IgniteTriFunction
    Modifier and Type | Method and Description
    --- | ---
    `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 IgniteTriFunction in org.apache.ignite.ml.dataset.impl.cache

    Methods in org.apache.ignite.ml.dataset.impl.cache with parameters of type IgniteTriFunction
    Modifier and Type | Method and Description
    --- | ---
    `<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 IgniteTriFunction in org.apache.ignite.ml.dataset.impl.local

    Methods in org.apache.ignite.ml.dataset.impl.local with parameters of type IgniteTriFunction
    Modifier and Type | Method and Description
    --- | ---
    `<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 IgniteTriFunction in org.apache.ignite.ml.dataset.primitive

    Methods in org.apache.ignite.ml.dataset.primitive with parameters of type IgniteTriFunction
    Modifier and Type | Method and Description
    --- | ---
    `<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.

  - ### Uses of IgniteTriFunction in org.apache.ignite.ml.math.functions

    Methods in org.apache.ignite.ml.math.functions that return IgniteTriFunction
    Modifier and Type | Method and Description
    --- | ---
    `default <V> IgniteTriFunction<A,B,C,V>` | IgniteTriFunction.`andThen(Function<? super R,? extends V> after)`

    Methods in org.apache.ignite.ml.math.functions with parameters of type IgniteTriFunction
    Modifier and Type | Method and Description
    --- | ---
    `static <A,B,C,D> IgniteCurriedTriFunction<A,B,C,D>` | Functions.`curry(IgniteTriFunction<A,B,C,D> f)` Transform tri-function of the form (a, b, c) -> d into a function of form a -> (b -> (c -> d)).

  - ### Uses of IgniteTriFunction in org.apache.ignite.ml.math.primitives.matrix

    Methods in org.apache.ignite.ml.math.primitives.matrix with parameters of type IgniteTriFunction
    Modifier and Type | Method and Description
    --- | ---
    `void` | Matrix.`compute(int row, int col, IgniteTriFunction<Integer,Integer,Double,Double> f)` Replace matrix entry with value oldVal at (row, col) with result of computing f(row, col, oldVal).
    `void` | AbstractMatrix.`compute(int row, int col, IgniteTriFunction<Integer,Integer,Double,Double> f)` Replace matrix entry with value oldVal at (row, col) with result of computing f(row, col, oldVal).

  - ### Uses of IgniteTriFunction in org.apache.ignite.ml.math.primitives.matrix.impl

    Methods in org.apache.ignite.ml.math.primitives.matrix.impl with parameters of type IgniteTriFunction
    Modifier and Type | Method and Description
    --- | ---
    `void` | SparseMatrix.`compute(int row, int col, IgniteTriFunction<Integer,Integer,Double,Double> f)` Replace matrix entry with value oldVal at (row, col) with result of computing f(row, col, oldVal).

  - ### Uses of IgniteTriFunction in org.apache.ignite.ml.math.primitives.matrix.storage

    Methods in org.apache.ignite.ml.math.primitives.matrix.storage with parameters of type IgniteTriFunction
    Modifier and Type | Method and Description
    --- | ---
    `void` | SparseMatrixStorage.`compute(int row, int col, IgniteTriFunction<Integer,Integer,Double,Double> f)`

  - ### Uses of IgniteTriFunction in org.apache.ignite.ml.math.util

    Methods in org.apache.ignite.ml.math.util with parameters of type IgniteTriFunction
    Modifier and Type | Method and Description
    --- | ---
    `static Vector` | MatrixUtil.`zipWith(Vector v1, Vector v2, IgniteTriFunction<Double,Double,Integer,Double> f)` Zip two vectors with given tri-function taking as third argument position in vector (i.e. apply binary function to both vector elementwise and construct vector from results).

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Release Date | : April 20 2022