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

- Packages that use IgniteDifferentiableVectorToDoubleFunction
  Package | Description
  --- | ---
  org.apache.ignite.ml.nn | Contains neural networks and related classes.
  org.apache.ignite.ml.optimization | Contains implementations of optimization algorithms and related classes.
  org.apache.ignite.ml.optimization.updatecalculators | Contains update calculators.

- - ### Uses of IgniteDifferentiableVectorToDoubleFunction in org.apache.ignite.ml.nn

    Methods in org.apache.ignite.ml.nn that return types with arguments of type IgniteDifferentiableVectorToDoubleFunction
    Modifier and Type | Method and Description
    --- | ---
    `IgniteFunction<Vector,IgniteDifferentiableVectorToDoubleFunction>` | MLPTrainer.`getLoss()` Get the loss function to be minimized during the training.

    Method parameters in org.apache.ignite.ml.nn with type arguments of type IgniteDifferentiableVectorToDoubleFunction
    Modifier and Type | Method and Description
    --- | ---
    `Vector` | MultilayerPerceptron.`differentiateByParameters(IgniteFunction<Vector,IgniteDifferentiableVectorToDoubleFunction> loss, Matrix inputsBatch, Matrix truthBatch)` Compose function in the following way: feed output of this model as input to second argument to loss function.
    `MLPTrainer<P>` | MLPTrainer.`withLoss(IgniteFunction<Vector,IgniteDifferentiableVectorToDoubleFunction> loss)` Set up the loss function to be minimized during the training.

    Constructor parameters in org.apache.ignite.ml.nn with type arguments of type IgniteDifferentiableVectorToDoubleFunction
    Constructor and Description
    `MLPTrainer(IgniteFunction<Dataset<EmptyContext,SimpleLabeledDatasetData>,MLPArchitecture> archSupplier, IgniteFunction<Vector,IgniteDifferentiableVectorToDoubleFunction> loss, UpdatesStrategy<? super MultilayerPerceptron,P> updatesStgy, int maxIterations, int batchSize, int locIterations, long seed)` Constructs a new instance of multilayer perceptron trainer.
    `MLPTrainer(MLPArchitecture arch, IgniteFunction<Vector,IgniteDifferentiableVectorToDoubleFunction> loss, UpdatesStrategy<? super MultilayerPerceptron,P> updatesStgy, int maxIterations, int batchSize, int locIterations, long seed)` Constructs a new instance of multilayer perceptron trainer.

  - ### Uses of IgniteDifferentiableVectorToDoubleFunction in org.apache.ignite.ml.optimization

    Fields in org.apache.ignite.ml.optimization with type parameters of type IgniteDifferentiableVectorToDoubleFunction
    Modifier and Type | Field and Description
    --- | ---
    `static IgniteFunction<Vector,IgniteDifferentiableVectorToDoubleFunction>` | LossFunctions.`HINGE` Hinge loss function.
    `static IgniteFunction<Vector,IgniteDifferentiableVectorToDoubleFunction>` | LossFunctions.`L1` L1 loss function.
    `static IgniteFunction<Vector,IgniteDifferentiableVectorToDoubleFunction>` | LossFunctions.`L2` L2 loss function.
    `static IgniteFunction<Vector,IgniteDifferentiableVectorToDoubleFunction>` | LossFunctions.`LOG` Log loss function.
    `static IgniteFunction<Vector,IgniteDifferentiableVectorToDoubleFunction>` | LossFunctions.`MSE` Mean squared error loss function.

    Method parameters in org.apache.ignite.ml.optimization with type arguments of type IgniteDifferentiableVectorToDoubleFunction
    Modifier and Type | Method and Description
    --- | ---
    `Vector` | SmoothParametrized.`differentiateByParameters(IgniteFunction<Vector,IgniteDifferentiableVectorToDoubleFunction> loss, Matrix inputsBatch, Matrix truthBatch)` Compose function in the following way: feed output of this model as input to second argument to loss function.

  - ### Uses of IgniteDifferentiableVectorToDoubleFunction in org.apache.ignite.ml.optimization.updatecalculators

    Fields in org.apache.ignite.ml.optimization.updatecalculators with type parameters of type IgniteDifferentiableVectorToDoubleFunction
    Modifier and Type | Field and Description
    --- | ---
    `protected IgniteFunction<Vector,IgniteDifferentiableVectorToDoubleFunction>` | RPropUpdateCalculator.`loss` Loss function.
    `protected IgniteFunction<Vector,IgniteDifferentiableVectorToDoubleFunction>` | SimpleGDUpdateCalculator.`loss` Loss function.

    Method parameters in org.apache.ignite.ml.optimization.updatecalculators with type arguments of type IgniteDifferentiableVectorToDoubleFunction
    Modifier and Type | Method and Description
    --- | ---
    `NesterovParameterUpdate` | NesterovUpdateCalculator.`init(M mdl, IgniteFunction<Vector,IgniteDifferentiableVectorToDoubleFunction> loss)` Initializes the update calculator.
    `P` | ParameterUpdateCalculator.`init(M mdl, IgniteFunction<Vector,IgniteDifferentiableVectorToDoubleFunction> loss)` Initializes the update calculator.
    `RPropParameterUpdate` | RPropUpdateCalculator.`init(SmoothParametrized mdl, IgniteFunction<Vector,IgniteDifferentiableVectorToDoubleFunction> loss)` Initializes the update calculator.
    `SimpleGDParameterUpdate` | SimpleGDUpdateCalculator.`init(SmoothParametrized mdl, IgniteFunction<Vector,IgniteDifferentiableVectorToDoubleFunction> loss)` Initializes the update calculator.

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Ignite Database and Caching Platform | : ver. 2.15.0
Release Date | : April 25 2023