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

Packages that use IgniteFunction

Package	Description
org.apache.ignite.ml	Root ML package.
org.apache.ignite.ml.clustering.kmeans	Contains kMeans clustering algorithm.
org.apache.ignite.ml.dataset	Base package for machine learning dataset classes.
org.apache.ignite.ml.dataset.impl.cache.util	Contains util classes used in cache based implementation of dataset.
org.apache.ignite.ml.knn.classification	Contains main APIs for kNN classification algorithms.
org.apache.ignite.ml.knn.regression	Contains helper classes for kNN regression algorithms.
org.apache.ignite.ml.math	Contains main APIs for distributed code algebra.
org.apache.ignite.ml.math.distributed	Contains classes for distribution support.
org.apache.ignite.ml.math.functions	Contains serializable functions for distributed code algebra.
org.apache.ignite.ml.math.impls.matrix	Contains several matrix implementations.
org.apache.ignite.ml.math.impls.storage.vector	Contains specific implementations for vector storage models.
org.apache.ignite.ml.math.impls.vector	Contains specific implementations for vectors.
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.
org.apache.ignite.ml.regressions.linear	Contains various linear regressions.
org.apache.ignite.ml.svm	Contains main APIs for SVM(support vector machines) algorithms.
org.apache.ignite.ml.tree	Root package for decision trees.

Uses of IgniteFunction in org.apache.ignite.ml

Subinterfaces of IgniteFunction in org.apache.ignite.ml

Modifier and Type	Interface and Description
interface	Model<T,V> Basic interface for all models.

Uses of IgniteFunction in org.apache.ignite.ml.clustering.kmeans

Subinterfaces of IgniteFunction in org.apache.ignite.ml.clustering.kmeans

Modifier and Type	Interface and Description
interface	ClusterizationModel<P,V> Base interface for all clusterization models.

Classes in org.apache.ignite.ml.clustering.kmeans that implement IgniteFunction

Modifier and Type	Class and Description
class	KMeansModel This class encapsulates result of clusterization by KMeans algorithm.

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

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

Modifier and Type	Method and Description
default <C2 extends Serializable> PartitionContextBuilder<K,V,C2>	PartitionContextBuilder.andThen(IgniteFunction<C,C2> fun) Makes a composed partition context builder that first builds a context and then applies the specified function on the result.
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 <I extends Dataset<C,D>> I	Dataset.wrap(IgniteFunction<Dataset<C,D>,I> wrapper) Wraps this dataset into the specified wrapper to introduce new functionality based on compute and computeWithCtx methods.

Uses of IgniteFunction in org.apache.ignite.ml.dataset.impl.cache.util

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

Modifier and Type	Method and Description
static <R> Collection<R>	ComputeUtils.affinityCallWithRetries(Ignite ignite, Collection<String> cacheNames, IgniteFunction<Integer,R> fun, int retries) Calls the specified fun function on all partitions so that is't guaranteed that partitions with the same index of all specified caches will be placed on the same node and will not be moved before computation is finished.
static <R> Collection<R>	ComputeUtils.affinityCallWithRetries(Ignite ignite, Collection<String> cacheNames, IgniteFunction<Integer,R> fun, int retries, int interval) Calls the specified fun function on all partitions so that is't guaranteed that partitions with the same index of all specified caches will be placed on the same node and will not be moved before computation is finished.

Uses of IgniteFunction in org.apache.ignite.ml.knn.classification

Classes in org.apache.ignite.ml.knn.classification that implement IgniteFunction

Modifier and Type	Class and Description
class	KNNClassificationModel<K,V> kNN algorithm model to solve multi-class classification task.

Uses of IgniteFunction in org.apache.ignite.ml.knn.regression

Classes in org.apache.ignite.ml.knn.regression that implement IgniteFunction

Modifier and Type	Class and Description
class	KNNRegressionModel<K,V> This class provides kNN Multiple Linear Regression or Locally [weighted] regression (Simple and Weighted versions).

Uses of IgniteFunction in org.apache.ignite.ml.math

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

Modifier and Type	Method and Description
Vector	Matrix.foldColumns(IgniteFunction<Vector,Double> fun) Collects the results of applying a given function to all columns in this matrix.
Vector	Matrix.foldRows(IgniteFunction<Vector,Double> fun) Collects the results of applying a given function to all rows in this matrix.

Constructors in org.apache.ignite.ml.math with parameters of type IgniteFunction

Constructor and Description
Isomorphism(IgniteFunction<K,V> forward, IgniteFunction<V,K> back) Build isomorphism with forward and backward functions.
Isomorphism(IgniteFunction<K,V> forward, IgniteFunction<V,K> back) Build isomorphism with forward and backward functions.

Uses of IgniteFunction in org.apache.ignite.ml.math.distributed

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

Modifier and Type	Method and Description
static <K,V> void	CacheUtils.map(String cacheName, KeyMapper<K> keyMapper, ValueMapper<V> valMapper, IgniteFunction<Double,Double> mapper)

Uses of IgniteFunction in org.apache.ignite.ml.math.functions

Subinterfaces of IgniteFunction in org.apache.ignite.ml.math.functions

Modifier and Type	Interface and Description
interface	IgniteCurriedBiFunction<A,B,T> Serializable binary function.
interface	IgniteCurriedTriFunction<A,B,C,D> Serializable curried tri-function.
interface	IgniteDifferentiableVectorToDoubleFunction Interface for differentiable functions from vector to double.

Methods in org.apache.ignite.ml.math.functions that return IgniteFunction

Modifier and Type	Method and Description
static <A,B> IgniteFunction<A,IgniteSupplier<B>>	Functions.outputSupplier(IgniteFunction<A,B> f) Transform function of form a -> b into a -> (() -> b).

Methods in org.apache.ignite.ml.math.functions with parameters of type IgniteFunction

Modifier and Type	Method and Description
default <V> IgniteBiFunction<T,U,V>	IgniteBiFunction.andThen(IgniteFunction<? super R,? extends V> after)
static <A,B extends Comparable<B>> IgniteBiTuple<Integer,A>	Functions.argmin(List<A> args, IgniteFunction<A,B> f)
static <A,B> IgniteFunction<A,IgniteSupplier<B>>	Functions.outputSupplier(IgniteFunction<A,B> f) Transform function of form a -> b into a -> (() -> b).

Uses of IgniteFunction in org.apache.ignite.ml.math.impls.matrix

Methods in org.apache.ignite.ml.math.impls.matrix with parameters of type IgniteFunction

Modifier and Type	Method and Description
Vector	AbstractMatrix.foldColumns(IgniteFunction<Vector,Double> fun) Collects the results of applying a given function to all columns in this matrix.
Vector	AbstractMatrix.foldRows(IgniteFunction<Vector,Double> fun) Collects the results of applying a given function to all rows in this matrix.

Uses of IgniteFunction in org.apache.ignite.ml.math.impls.storage.vector

Methods in org.apache.ignite.ml.math.impls.storage.vector that return IgniteFunction

Modifier and Type	Method and Description
IgniteFunction<Integer,Double>	FunctionVectorStorage.getFunction()

Constructors in org.apache.ignite.ml.math.impls.storage.vector with parameters of type IgniteFunction

Constructor and Description
FunctionVectorStorage(int size, IgniteFunction<Integer,Double> getFunc) Creates read-only storage.
FunctionVectorStorage(int size, IgniteFunction<Integer,Double> getFunc, IntDoubleToVoidFunction setFunc) Creates read-only or read-write storage.

Uses of IgniteFunction in org.apache.ignite.ml.math.impls.vector

Constructors in org.apache.ignite.ml.math.impls.vector with parameters of type IgniteFunction

Constructor and Description
FunctionVector(int size, IgniteFunction<Integer,Double> getFunc) Creates read-only function vector.
FunctionVector(int size, IgniteFunction<Integer,Double> getFunc, IntDoubleToVoidFunction setFunc) Creates read-write or read-only function vector.

Uses of IgniteFunction in org.apache.ignite.ml.nn

Classes in org.apache.ignite.ml.nn that implement IgniteFunction

Modifier and Type	Class and Description
class	MultilayerPerceptron Class encapsulating logic of multilayer perceptron.

Methods in org.apache.ignite.ml.nn that return IgniteFunction

Modifier and Type	Method and Description
IgniteFunction<List<U>,U>	UpdatesStrategy.allUpdatesReducer() Get function used to reduce updates from different trainings (for example, averaging of gradients of all parallel trainings).
IgniteFunction<List<U>,U>	UpdatesStrategy.locStepUpdatesReducer() Get function used to reduce updates in one training (for example, sum all sequential gradient updates to get one gradient update).

Methods in org.apache.ignite.ml.nn with parameters of type IgniteFunction

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.

Constructors in org.apache.ignite.ml.nn with parameters of type IgniteFunction

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(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.
UpdatesStrategy(ParameterUpdateCalculator<M,U> updatesCalculator, IgniteFunction<List<U>,U> locStepUpdatesReducer, IgniteFunction<List<U>,U> allUpdatesReducer) Construct instance of this class with given parameters.
UpdatesStrategy(ParameterUpdateCalculator<M,U> updatesCalculator, IgniteFunction<List<U>,U> locStepUpdatesReducer, IgniteFunction<List<U>,U> allUpdatesReducer) Construct instance of this class with given parameters.

Uses of IgniteFunction in org.apache.ignite.ml.optimization

Subinterfaces of IgniteFunction in org.apache.ignite.ml.optimization

Modifier and Type	Interface and Description
interface	SmoothParametrized<M extends Parametrized<M>> Interface for models which are smooth functions of their parameters.

Fields in org.apache.ignite.ml.optimization declared as IgniteFunction

Modifier and Type	Field and Description
static IgniteFunction<Vector,IgniteDifferentiableVectorToDoubleFunction>	LossFunctions.MSE Mean squared error loss function.

Methods in org.apache.ignite.ml.optimization with parameters of type IgniteFunction

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 IgniteFunction in org.apache.ignite.ml.optimization.updatecalculators

Fields in org.apache.ignite.ml.optimization.updatecalculators declared as IgniteFunction

Modifier and Type	Field and Description
protected IgniteFunction<Vector,IgniteDifferentiableVectorToDoubleFunction>	SimpleGDUpdateCalculator.loss Loss function.
protected IgniteFunction<Vector,IgniteDifferentiableVectorToDoubleFunction>	RPropUpdateCalculator.loss Loss function.

Methods in org.apache.ignite.ml.optimization.updatecalculators with parameters of type IgniteFunction

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.
SimpleGDParameterUpdate	SimpleGDUpdateCalculator.init(SmoothParametrized mdl, IgniteFunction<Vector,IgniteDifferentiableVectorToDoubleFunction> loss) Initializes the update calculator.
RPropParameterUpdate	RPropUpdateCalculator.init(SmoothParametrized mdl, IgniteFunction<Vector,IgniteDifferentiableVectorToDoubleFunction> loss) Initializes the update calculator.

Uses of IgniteFunction in org.apache.ignite.ml.regressions.linear

Classes in org.apache.ignite.ml.regressions.linear that implement IgniteFunction

Modifier and Type	Class and Description
class	LinearRegressionModel Simple linear regression model which predicts result value Y as a linear combination of input variables: Y = weights * X + intercept.

Uses of IgniteFunction in org.apache.ignite.ml.svm

Classes in org.apache.ignite.ml.svm that implement IgniteFunction

Modifier and Type	Class and Description
class	SVMLinearBinaryClassificationModel Base class for SVM linear classification model.
class	SVMLinearMultiClassClassificationModel Base class for multi-classification model for set of SVM classifiers.

Uses of IgniteFunction in org.apache.ignite.ml.tree

Subinterfaces of IgniteFunction in org.apache.ignite.ml.tree

Modifier and Type	Interface and Description
interface	DecisionTreeNode Base interface for decision tree nodes.

Classes in org.apache.ignite.ml.tree that implement IgniteFunction

Modifier and Type	Class and Description
class	DecisionTreeConditionalNode Decision tree conditional (non-leaf) node.
class	DecisionTreeLeafNode Decision tree leaf node which contains value.