Uses of Interface
org.apache.ignite.ml.dataset.Dataset

Packages that use Dataset

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.knn	Contains main APIs for kNN algorithms.
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.nn	Contains neural networks and related classes.
org.apache.ignite.ml.tree.leaf	Root package for decision trees leaf builders.

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

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

Modifier and Type	Method and Description
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.

Methods in org.apache.ignite.ml.dataset that return Dataset

Modifier and Type	Method and Description
<C extends Serializable,D extends AutoCloseable> Dataset<C,D>	DatasetBuilder.build(PartitionContextBuilder<K,V,C> partCtxBuilder, PartitionDataBuilder<K,V,C,D> partDataBuilder) Constructs a new instance of Dataset that includes allocation required data structures and initialization of context part of partitions.
static <K,V,C extends Serializable,D extends AutoCloseable> Dataset<C,D>	DatasetFactory.create(DatasetBuilder<K,V> datasetBuilder, PartitionContextBuilder<K,V,C> partCtxBuilder, PartitionDataBuilder<K,V,C,D> partDataBuilder) Creates a new instance of distributed dataset using the specified partCtxBuilder and partDataBuilder.
static <K,V,C extends Serializable,D extends AutoCloseable> Dataset<C,D>	DatasetFactory.create(Ignite ignite, IgniteCache<K,V> upstreamCache, PartitionContextBuilder<K,V,C> partCtxBuilder, PartitionDataBuilder<K,V,C,D> partDataBuilder) Creates a new instance of distributed dataset using the specified partCtxBuilder and partDataBuilder.
static <K,V,C extends Serializable,D extends AutoCloseable> Dataset<C,D>	DatasetFactory.create(Map<K,V> upstreamMap, int partitions, PartitionContextBuilder<K,V,C> partCtxBuilder, PartitionDataBuilder<K,V,C,D> partDataBuilder) Creates a new instance of local dataset using the specified partCtxBuilder and partDataBuilder.

Method parameters in org.apache.ignite.ml.dataset with type arguments of type Dataset

Modifier and Type	Method and Description
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 Dataset in org.apache.ignite.ml.dataset.impl.cache

Classes in org.apache.ignite.ml.dataset.impl.cache that implement Dataset

Modifier and Type	Class and Description
class	CacheBasedDataset<K,V,C extends Serializable,D extends AutoCloseable> An implementation of dataset based on Ignite Cache, which is used as upstream and as reliable storage for partition context as well.

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

Classes in org.apache.ignite.ml.dataset.impl.local that implement Dataset

Modifier and Type	Class and Description
class	LocalDataset<C extends Serializable,D extends AutoCloseable> An implementation of dataset based on local data structures such as Map and List and doesn't requires Ignite environment.

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

Classes in org.apache.ignite.ml.dataset.primitive that implement Dataset

Modifier and Type	Class and Description
class	DatasetWrapper<C extends Serializable,D extends AutoCloseable> A dataset wrapper that allows to introduce new functionality based on common compute methods.
class	SimpleDataset<C extends Serializable> A simple dataset introduces additional methods based on a matrix of features.
class	SimpleLabeledDataset<C extends Serializable> A simple labeled dataset introduces additional methods based on a matrix of features and labels vector.

Fields in org.apache.ignite.ml.dataset.primitive declared as Dataset

Modifier and Type	Field and Description
protected Dataset<C,D>	DatasetWrapper.delegate Delegate that performs compute actions.

Constructors in org.apache.ignite.ml.dataset.primitive with parameters of type Dataset

Constructor and Description
DatasetWrapper(Dataset<C,D> delegate) Constructs a new instance of dataset wrapper that delegates compute actions to the actual delegate.
SimpleDataset(Dataset<C,SimpleDatasetData> delegate) Creates a new instance of simple dataset that introduces additional methods based on a matrix of features.
SimpleLabeledDataset(Dataset<C,SimpleLabeledDatasetData> delegate) Creates a new instance of simple labeled dataset that introduces additional methods based on a matrix of features and labels vector.

Uses of Dataset in org.apache.ignite.ml.knn

Methods in org.apache.ignite.ml.knn that return Dataset

Modifier and Type	Method and Description
static <K,V> Dataset<EmptyContext,LabeledDataset<Double,LabeledVector>>	KNNUtils.buildDataset(DatasetBuilder<K,V> datasetBuilder, IgniteBiFunction<K,V,double[]> featureExtractor, IgniteBiFunction<K,V,Double> lbExtractor) Builds dataset.

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

Constructors in org.apache.ignite.ml.knn.classification with parameters of type Dataset

Constructor and Description
KNNClassificationModel(Dataset<EmptyContext,LabeledDataset<Double,LabeledVector>> dataset) Builds the model via prepared dataset.

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

Constructors in org.apache.ignite.ml.knn.regression with parameters of type Dataset

Constructor and Description
KNNRegressionModel(Dataset<EmptyContext,LabeledDataset<Double,LabeledVector>> dataset) Builds the model via prepared dataset.

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

Constructor parameters in org.apache.ignite.ml.nn with type arguments of type Dataset

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.

Uses of Dataset in org.apache.ignite.ml.tree.leaf

Methods in org.apache.ignite.ml.tree.leaf with parameters of type Dataset

Modifier and Type	Method and Description
DecisionTreeLeafNode	MeanDecisionTreeLeafBuilder.createLeafNode(Dataset<EmptyContext,DecisionTreeData> dataset, TreeFilter pred) Creates new leaf node for given dataset and node predicate.
DecisionTreeLeafNode	DecisionTreeLeafBuilder.createLeafNode(Dataset<EmptyContext,DecisionTreeData> dataset, TreeFilter pred) Creates new leaf node for given dataset and node predicate.
DecisionTreeLeafNode	MostCommonDecisionTreeLeafBuilder.createLeafNode(Dataset<EmptyContext,DecisionTreeData> dataset, TreeFilter pred) Creates new leaf node for given dataset and node predicate.