Uses of Interface
org.apache.ignite.ml.environment.LearningEnvironmentBuilder

Packages that use LearningEnvironmentBuilder

Package	Description
org.apache.ignite.ml.clustering.kmeans	Contains kMeans clustering algorithm.
org.apache.ignite.ml.composition.bagging	Contains bootstrap aggregation (bagging) trainer allowing to combine some other trainers and return a bagged version of them.
org.apache.ignite.ml.composition.boosting	Contains Gradient Boosting regression and classification abstract classes allowing regressor type selecting in child classes.
org.apache.ignite.ml.composition.boosting.convergence	Package contains implementation of convergency checking algorithms for gradient boosting.
org.apache.ignite.ml.composition.boosting.convergence.simple	Contains implementation of Stub for convergence checking.
org.apache.ignite.ml.composition.stacking	Contains classes used for training with stacking technique.
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.cache.util	Contains util classes used in cache based implementation of dataset.
org.apache.ignite.ml.dataset.impl.local	Base package for local implementation of machine learning dataset.
org.apache.ignite.ml.environment	Package contains environment utils for ML algorithms.
org.apache.ignite.ml.knn.ann	Contains main APIs for ANN classification algorithms.
org.apache.ignite.ml.knn.utils	Contains util functionality for kNN algorithms.
org.apache.ignite.ml.math.isolve.lsqr	Contains LSQR algorithm implementation.
org.apache.ignite.ml.naivebayes.gaussian	Contains Gaussian naive Bayes classifier.
org.apache.ignite.ml.nn	Contains neural networks and related classes.
org.apache.ignite.ml.pipeline	Contains Pipeline API.
org.apache.ignite.ml.preprocessing	Base package for machine learning preprocessing classes.
org.apache.ignite.ml.preprocessing.binarization	Contains binarization preprocessor.
org.apache.ignite.ml.preprocessing.encoding	Contains encoding preprocessors.
org.apache.ignite.ml.preprocessing.imputing	Contains Imputer preprocessor.
org.apache.ignite.ml.preprocessing.maxabsscaling	Contains Max Abs Scaler preprocessor.
org.apache.ignite.ml.preprocessing.minmaxscaling	Contains Min Max Scaler preprocessor.
org.apache.ignite.ml.preprocessing.normalization	Contains Normalizer preprocessor.
org.apache.ignite.ml.preprocessing.standardscaling	Contains Standard scaler preprocessor.
org.apache.ignite.ml.recommendation	Contains recommendation system framework.
org.apache.ignite.ml.selection.cv	Root package for cross-validation algorithms.
org.apache.ignite.ml.trainers	Contains model trainers.
org.apache.ignite.ml.tree	Root package for decision trees.
org.apache.ignite.ml.tree.boosting	Contains implementation of gradient boosting on trees.
org.apache.ignite.ml.tree.randomforest	Contains random forest implementation classes.

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

Methods in org.apache.ignite.ml.clustering.kmeans with parameters of type LearningEnvironmentBuilder

Modifier and Type	Method and Description
KMeansTrainer	KMeansTrainer.withEnvironmentBuilder(LearningEnvironmentBuilder envBuilder) Changes learning Environment.

Uses of LearningEnvironmentBuilder in org.apache.ignite.ml.composition.bagging

Methods in org.apache.ignite.ml.composition.bagging with parameters of type LearningEnvironmentBuilder

Modifier and Type	Method and Description
BaggedTrainer<L>	BaggedTrainer.withEnvironmentBuilder(LearningEnvironmentBuilder envBuilder) Changes learning Environment.

Uses of LearningEnvironmentBuilder in org.apache.ignite.ml.composition.boosting

Fields in org.apache.ignite.ml.composition.boosting declared as LearningEnvironmentBuilder

Modifier and Type	Field and Description
protected LearningEnvironmentBuilder	GDBLearningStrategy.envBuilder Learning environment builder.

Methods in org.apache.ignite.ml.composition.boosting with parameters of type LearningEnvironmentBuilder

Modifier and Type	Method and Description
protected <V,K,C extends Serializable> IgniteBiTuple<Double,Long>	GDBTrainer.computeInitialValue(LearningEnvironmentBuilder envBuilder, DatasetBuilder<K,V> builder, Preprocessor<K,V> preprocessor) Compute mean value of label as first approximation.
GDBLearningStrategy	GDBLearningStrategy.withEnvironmentBuilder(LearningEnvironmentBuilder envBuilder) Sets learning environment.
GDBTrainer	GDBTrainer.withEnvironmentBuilder(LearningEnvironmentBuilder envBuilder) Changes learning Environment.
GDBRegressionTrainer	GDBRegressionTrainer.withEnvironmentBuilder(LearningEnvironmentBuilder envBuilder) Changes learning Environment.
GDBBinaryClassifierOnTreesTrainer	GDBBinaryClassifierTrainer.withEnvironmentBuilder(LearningEnvironmentBuilder envBuilder) Changes learning Environment.

Uses of LearningEnvironmentBuilder in org.apache.ignite.ml.composition.boosting.convergence

Methods in org.apache.ignite.ml.composition.boosting.convergence with parameters of type LearningEnvironmentBuilder

Modifier and Type	Method and Description
boolean	ConvergenceChecker.isConverged(LearningEnvironmentBuilder envBuilder, DatasetBuilder<K,V> datasetBuilder, ModelsComposition currMdl) Checks convergency on dataset.

Uses of LearningEnvironmentBuilder in org.apache.ignite.ml.composition.boosting.convergence.simple

Methods in org.apache.ignite.ml.composition.boosting.convergence.simple with parameters of type LearningEnvironmentBuilder

Modifier and Type	Method and Description
boolean	ConvergenceCheckerStub.isConverged(LearningEnvironmentBuilder envBuilder, DatasetBuilder<K,V> datasetBuilder, ModelsComposition currMdl) Checks convergency on dataset.

Uses of LearningEnvironmentBuilder in org.apache.ignite.ml.composition.stacking

Methods in org.apache.ignite.ml.composition.stacking with parameters of type LearningEnvironmentBuilder

Modifier and Type	Method and Description
StackedDatasetTrainer<IS,IA,O,AM,L>	StackedDatasetTrainer.withEnvironmentBuilder(LearningEnvironmentBuilder envBuilder) Changes learning Environment.
StackedVectorDatasetTrainer<O,AM,L>	StackedVectorDatasetTrainer.withEnvironmentBuilder(LearningEnvironmentBuilder envBuilder) Changes learning Environment.
SimpleStackedDatasetTrainer<I,O,AM,L>	SimpleStackedDatasetTrainer.withEnvironmentBuilder(LearningEnvironmentBuilder envBuilder) Changes learning Environment.

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

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

Modifier and Type	Method and Description
<C extends Serializable,D extends AutoCloseable> Dataset<C,D>	DatasetBuilder.build(LearningEnvironmentBuilder envBuilder, PartitionContextBuilder<K,V,C> partCtxBuilder, PartitionDataBuilder<K,V,C,D> partDataBuilder, LearningEnvironment localLearningEnv) 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, LearningEnvironmentBuilder envBuilder, PartitionContextBuilder<K,V,C> partCtxBuilder, PartitionDataBuilder<K,V,C,D> partDataBuilder, LearningEnvironment environment) 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, LearningEnvironmentBuilder envBuilder, PartitionContextBuilder<K,V,C> partCtxBuilder, PartitionDataBuilder<K,V,C,D> partDataBuilder, LearningEnvironment environment) 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, LearningEnvironmentBuilder envBuilder, int partitions, PartitionContextBuilder<K,V,C> partCtxBuilder, PartitionDataBuilder<K,V,C,D> partDataBuilder, LearningEnvironment environment) Creates a new instance of local dataset using the specified partCtxBuilder and partDataBuilder.
static <K,V,C extends Serializable,CO extends Serializable> SimpleDataset<C>	DatasetFactory.createSimpleDataset(DatasetBuilder<K,V> datasetBuilder, LearningEnvironmentBuilder envBuilder, PartitionContextBuilder<K,V,C> partCtxBuilder, Preprocessor<K,V> featureExtractor) Creates a new instance of distributed SimpleDataset using the specified partCtxBuilder and featureExtractor.
static <K,V,CO extends Serializable> SimpleDataset<EmptyContext>	DatasetFactory.createSimpleDataset(DatasetBuilder<K,V> datasetBuilder, LearningEnvironmentBuilder envBuilder, Preprocessor<K,V> featureExtractor) Creates a new instance of distributed SimpleDataset using the specified featureExtractor.
static <K,V,C extends Serializable,CO extends Serializable> SimpleDataset<C>	DatasetFactory.createSimpleDataset(Ignite ignite, IgniteCache<K,V> upstreamCache, LearningEnvironmentBuilder envBuilder, PartitionContextBuilder<K,V,C> partCtxBuilder, Preprocessor<K,V> featureExtractor) Creates a new instance of distributed SimpleDataset using the specified partCtxBuilder and featureExtractor.
static <K,V,CO extends Serializable> SimpleDataset<EmptyContext>	DatasetFactory.createSimpleDataset(Ignite ignite, IgniteCache<K,V> upstreamCache, LearningEnvironmentBuilder envBuilder, Preprocessor<K,V> featureExtractor) Creates a new instance of distributed SimpleDataset using the specified featureExtractor.
static <K,V,C extends Serializable,CO extends Serializable> SimpleDataset<C>	DatasetFactory.createSimpleDataset(Map<K,V> upstreamMap, int partitions, LearningEnvironmentBuilder envBuilder, PartitionContextBuilder<K,V,C> partCtxBuilder, Preprocessor<K,V> featureExtractor) Creates a new instance of local SimpleDataset using the specified partCtxBuilder and featureExtractor.
static <K,V,CO extends Serializable> SimpleDataset<EmptyContext>	DatasetFactory.createSimpleDataset(Map<K,V> upstreamMap, int partitions, LearningEnvironmentBuilder envBuilder, Preprocessor<K,V> featureExtractor) Creates a new instance of local SimpleDataset using the specified featureExtractor.
static <K,V,C extends Serializable,CO extends Serializable> SimpleLabeledDataset<C>	DatasetFactory.createSimpleLabeledDataset(DatasetBuilder<K,V> datasetBuilder, LearningEnvironmentBuilder envBuilder, PartitionContextBuilder<K,V,C> partCtxBuilder, Preprocessor<K,V> vectorizer) Creates a new instance of distributed SimpleLabeledDataset using the specified partCtxBuilder, featureExtractor and lbExtractor.
static <K,V,CO extends Serializable> SimpleLabeledDataset<EmptyContext>	DatasetFactory.createSimpleLabeledDataset(DatasetBuilder<K,V> datasetBuilder, LearningEnvironmentBuilder envBuilder, Preprocessor<K,V> vectorizer) Creates a new instance of distributed SimpleLabeledDataset using the specified featureExtractor and lbExtractor.
static <K,V,C extends Serializable,CO extends Serializable> SimpleLabeledDataset<C>	DatasetFactory.createSimpleLabeledDataset(Ignite ignite, IgniteCache<K,V> upstreamCache, LearningEnvironmentBuilder envBuilder, PartitionContextBuilder<K,V,C> partCtxBuilder, Preprocessor<K,V> vectorizer) Creates a new instance of distributed SimpleLabeledDataset using the specified partCtxBuilder, featureExtractor and lbExtractor.
static <K,V,CO extends Serializable> SimpleLabeledDataset<EmptyContext>	DatasetFactory.createSimpleLabeledDataset(Ignite ignite, LearningEnvironmentBuilder envBuilder, IgniteCache<K,V> upstreamCache, Preprocessor<K,V> vectorizer) Creates a new instance of distributed SimpleLabeledDataset using the specified featureExtractor and lbExtractor.
static <K,V,C extends Serializable,CO extends Serializable> SimpleLabeledDataset<C>	DatasetFactory.createSimpleLabeledDataset(Map<K,V> upstreamMap, int partitions, LearningEnvironmentBuilder envBuilder, PartitionContextBuilder<K,V,C> partCtxBuilder, Preprocessor<K,V> vectorizer) Creates a new instance of local SimpleLabeledDataset using the specified partCtxBuilder, featureExtractor and lbExtractor.
static <K,V,CO extends Serializable> SimpleLabeledDataset<EmptyContext>	DatasetFactory.createSimpleLabeledDataset(Map<K,V> upstreamMap, LearningEnvironmentBuilder envBuilder, int partitions, Preprocessor<K,V> vectorizer) Creates a new instance of local SimpleLabeledDataset using the specified featureExtractor and lbExtractor.

Uses of LearningEnvironmentBuilder in org.apache.ignite.ml.dataset.impl.cache

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

Modifier and Type	Method and Description
<C extends Serializable,D extends AutoCloseable> CacheBasedDataset<K,V,C,D>	CacheBasedDatasetBuilder.build(LearningEnvironmentBuilder envBuilder, PartitionContextBuilder<K,V,C> partCtxBuilder, PartitionDataBuilder<K,V,C,D> partDataBuilder, LearningEnvironment localLearningEnv) Constructs a new instance of Dataset that includes allocation required data structures and initialization of context part of partitions.

Constructors in org.apache.ignite.ml.dataset.impl.cache with parameters of type LearningEnvironmentBuilder

Constructor and Description

CacheBasedDataset(Ignite ignite, IgniteCache<K,V> upstreamCache, IgniteBiPredicate<K,V> filter, UpstreamTransformerBuilder upstreamTransformerBuilder, IgniteCache<Integer,C> datasetCache, LearningEnvironmentBuilder envBuilder, PartitionDataBuilder<K,V,C,D> partDataBuilder, UUID datasetId, boolean upstreamKeepBinary, LearningEnvironment localLearningEnv, int retriesCnt) Constructs a new instance of dataset based on Ignite Cache, which is used as upstream and as reliable storage for partition context as well.

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

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

Modifier and Type	Method and Description
static LearningEnvironment	ComputeUtils.getLearningEnvironment(Ignite ignite, UUID datasetId, int part, LearningEnvironmentBuilder envBuilder) Gets learning environment for given partition.
static <K,V,C extends Serializable> void	ComputeUtils.initContext(Ignite ignite, String upstreamCacheName, UpstreamTransformerBuilder transformerBuilder, IgniteBiPredicate<K,V> filter, String datasetCacheName, PartitionContextBuilder<K,V,C> ctxBuilder, LearningEnvironmentBuilder envBuilder, int retries, int interval, boolean isKeepBinary, DeployingContext deployingContext) Initializes partition context by loading it from a partition upstream.

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

Methods in org.apache.ignite.ml.dataset.impl.local with parameters of type LearningEnvironmentBuilder

Modifier and Type	Method and Description
<C extends Serializable,D extends AutoCloseable> LocalDataset<C,D>	LocalDatasetBuilder.build(LearningEnvironmentBuilder envBuilder, PartitionContextBuilder<K,V,C> partCtxBuilder, PartitionDataBuilder<K,V,C,D> partDataBuilder, LearningEnvironment learningEnvironment) Constructs a new instance of Dataset that includes allocation required data structures and initialization of context part of partitions.

Uses of LearningEnvironmentBuilder in org.apache.ignite.ml.environment

Classes in org.apache.ignite.ml.environment that implement LearningEnvironmentBuilder

Modifier and Type	Class and Description
class	DefaultLearningEnvironmentBuilder Builder for LearningEnvironment.

Methods in org.apache.ignite.ml.environment that return LearningEnvironmentBuilder

Modifier and Type	Method and Description
static LearningEnvironmentBuilder	LearningEnvironmentBuilder.defaultBuilder() Get default LearningEnvironmentBuilder.
LearningEnvironmentBuilder	DefaultLearningEnvironmentBuilder.withDataTtl(long dataTtl) Specify partition data time-to-live in seconds (-1 for an infinite lifetime).
LearningEnvironmentBuilder	LearningEnvironmentBuilder.withDataTtl(long dataTtl) Specify partition data time-to-live in seconds (-1 for an infinite lifetime).
default <T extends MLLogger.Factory & Serializable> LearningEnvironmentBuilder	LearningEnvironmentBuilder.withLoggingFactory(T loggingFactory) Specify logging factory.
LearningEnvironmentBuilder	LearningEnvironmentBuilder.withLoggingFactoryDependency(IgniteFunction<Integer,MLLogger.Factory> loggingFactory) Specify dependency (partition -> logging factory).
default <T extends ParallelismStrategy & Serializable> LearningEnvironmentBuilder	LearningEnvironmentBuilder.withParallelismStrategy(T stgy) Specifies Parallelism Strategy for LearningEnvironment.
LearningEnvironmentBuilder	LearningEnvironmentBuilder.withParallelismStrategyDependency(IgniteFunction<Integer,ParallelismStrategy> stgy) Specifies dependency (partition -> Parallelism Strategy for LearningEnvironment).
default LearningEnvironmentBuilder	LearningEnvironmentBuilder.withParallelismStrategyType(ParallelismStrategy.Type stgyType) Specifies Parallelism Strategy Type for LearningEnvironment.
LearningEnvironmentBuilder	LearningEnvironmentBuilder.withParallelismStrategyTypeDependency(IgniteFunction<Integer,ParallelismStrategy.Type> stgyType) Specifies dependency (partition -> Parallelism Strategy Type for LearningEnvironment).
default LearningEnvironmentBuilder	LearningEnvironmentBuilder.withRandom(Random random) Specify random numbers generator for learning environment.
LearningEnvironmentBuilder	DefaultLearningEnvironmentBuilder.withRandomDependency(IgniteFunction<Integer,Random> rngSupplier) Specify dependency (partition -> random numbers generator).
LearningEnvironmentBuilder	LearningEnvironmentBuilder.withRandomDependency(IgniteFunction<Integer,Random> rngSupplier) Specify dependency (partition -> random numbers generator).
default LearningEnvironmentBuilder	LearningEnvironmentBuilder.withRNGSeed(long seed) Specify seed for random number generator.
LearningEnvironmentBuilder	DefaultLearningEnvironmentBuilder.withRNGSeedDependency(IgniteFunction<Integer,Long> seed) Specify dependency (partition -> seed for random number generator).
LearningEnvironmentBuilder	LearningEnvironmentBuilder.withRNGSeedDependency(IgniteFunction<Integer,Long> seed) Specify dependency (partition -> seed for random number generator).

Uses of LearningEnvironmentBuilder in org.apache.ignite.ml.knn.ann

Methods in org.apache.ignite.ml.knn.ann with parameters of type LearningEnvironmentBuilder

Modifier and Type	Method and Description
ANNClassificationTrainer	ANNClassificationTrainer.withEnvironmentBuilder(LearningEnvironmentBuilder envBuilder) Changes learning Environment.

Uses of LearningEnvironmentBuilder in org.apache.ignite.ml.knn.utils

Methods in org.apache.ignite.ml.knn.utils with parameters of type LearningEnvironmentBuilder

Modifier and Type	Method and Description
static <K,V,C extends Serializable> Dataset<EmptyContext,LabeledVectorSet<LabeledVector>>	KNNUtils.buildDataset(LearningEnvironmentBuilder envBuilder, DatasetBuilder<K,V> datasetBuilder, Preprocessor<K,V> vectorizer) Builds dataset.

Uses of LearningEnvironmentBuilder in org.apache.ignite.ml.math.isolve.lsqr

Constructors in org.apache.ignite.ml.math.isolve.lsqr with parameters of type LearningEnvironmentBuilder

Constructor and Description
LSQROnHeap(DatasetBuilder<K,V> datasetBuilder, LearningEnvironmentBuilder envBuilder, PartitionDataBuilder<K,V,LSQRPartitionContext,SimpleLabeledDatasetData> partDataBuilder, LearningEnvironment localLearningEnv) Constructs a new instance of OnHeap LSQR algorithm implementation.

Uses of LearningEnvironmentBuilder in org.apache.ignite.ml.naivebayes.gaussian

Methods in org.apache.ignite.ml.naivebayes.gaussian with parameters of type LearningEnvironmentBuilder

Modifier and Type	Method and Description
GaussianNaiveBayesTrainer	GaussianNaiveBayesTrainer.withEnvironmentBuilder(LearningEnvironmentBuilder envBuilder) Changes learning Environment.

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

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

Modifier and Type	Method and Description
MLPTrainer<P>	MLPTrainer.withEnvironmentBuilder(LearningEnvironmentBuilder envBuilder) Changes learning Environment.

Uses of LearningEnvironmentBuilder in org.apache.ignite.ml.pipeline

Methods in org.apache.ignite.ml.pipeline with parameters of type LearningEnvironmentBuilder

Modifier and Type	Method and Description
void	Pipeline.setEnvironmentBuilder(LearningEnvironmentBuilder envBuilder) Set learning environment builder.

Uses of LearningEnvironmentBuilder in org.apache.ignite.ml.preprocessing

Methods in org.apache.ignite.ml.preprocessing with parameters of type LearningEnvironmentBuilder

Modifier and Type	Method and Description
Preprocessor<K,V>	PreprocessingTrainer.fit(LearningEnvironmentBuilder envBuilder, DatasetBuilder<K,V> datasetBuilder, Preprocessor<K,V> basePreprocessor) Fits preprocessor.
default Preprocessor<K,V>	PreprocessingTrainer.fit(LearningEnvironmentBuilder envBuilder, Ignite ignite, IgniteCache<K,V> cache, Preprocessor<K,V> basePreprocessor) Fits preprocessor.
default Preprocessor<K,V>	PreprocessingTrainer.fit(LearningEnvironmentBuilder envBuilder, Map<K,V> data, int parts, Preprocessor<K,V> basePreprocessor) Fits preprocessor.

Uses of LearningEnvironmentBuilder in org.apache.ignite.ml.preprocessing.binarization

Methods in org.apache.ignite.ml.preprocessing.binarization with parameters of type LearningEnvironmentBuilder

Modifier and Type	Method and Description
BinarizationPreprocessor<K,V>	BinarizationTrainer.fit(LearningEnvironmentBuilder envBuilder, DatasetBuilder<K,V> datasetBuilder, Preprocessor<K,V> basePreprocessor) Fits preprocessor.

Uses of LearningEnvironmentBuilder in org.apache.ignite.ml.preprocessing.encoding

Methods in org.apache.ignite.ml.preprocessing.encoding with parameters of type LearningEnvironmentBuilder

Modifier and Type	Method and Description
EncoderPreprocessor<K,V>	EncoderTrainer.fit(LearningEnvironmentBuilder envBuilder, DatasetBuilder<K,V> datasetBuilder, Preprocessor<K,V> basePreprocessor) Fits preprocessor.

Uses of LearningEnvironmentBuilder in org.apache.ignite.ml.preprocessing.imputing

Methods in org.apache.ignite.ml.preprocessing.imputing with parameters of type LearningEnvironmentBuilder

Modifier and Type	Method and Description
ImputerPreprocessor<K,V>	ImputerTrainer.fit(LearningEnvironmentBuilder envBuilder, DatasetBuilder<K,V> datasetBuilder, Preprocessor<K,V> basePreprocessor) Fits preprocessor.

Uses of LearningEnvironmentBuilder in org.apache.ignite.ml.preprocessing.maxabsscaling

Methods in org.apache.ignite.ml.preprocessing.maxabsscaling with parameters of type LearningEnvironmentBuilder

Modifier and Type	Method and Description
MaxAbsScalerPreprocessor<K,V>	MaxAbsScalerTrainer.fit(LearningEnvironmentBuilder envBuilder, DatasetBuilder<K,V> datasetBuilder, Preprocessor<K,V> basePreprocessor) Fits preprocessor.

Uses of LearningEnvironmentBuilder in org.apache.ignite.ml.preprocessing.minmaxscaling

Methods in org.apache.ignite.ml.preprocessing.minmaxscaling with parameters of type LearningEnvironmentBuilder

Modifier and Type	Method and Description
MinMaxScalerPreprocessor<K,V>	MinMaxScalerTrainer.fit(LearningEnvironmentBuilder envBuilder, DatasetBuilder<K,V> datasetBuilder, Preprocessor<K,V> basePreprocessor) Fits preprocessor.

Uses of LearningEnvironmentBuilder in org.apache.ignite.ml.preprocessing.normalization

Methods in org.apache.ignite.ml.preprocessing.normalization with parameters of type LearningEnvironmentBuilder

Modifier and Type	Method and Description
NormalizationPreprocessor<K,V>	NormalizationTrainer.fit(LearningEnvironmentBuilder envBuilder, DatasetBuilder<K,V> datasetBuilder, Preprocessor<K,V> basePreprocessor) Fits preprocessor.

Uses of LearningEnvironmentBuilder in org.apache.ignite.ml.preprocessing.standardscaling

Methods in org.apache.ignite.ml.preprocessing.standardscaling with parameters of type LearningEnvironmentBuilder

Modifier and Type	Method and Description
StandardScalerPreprocessor<K,V>	StandardScalerTrainer.fit(LearningEnvironmentBuilder envBuilder, DatasetBuilder<K,V> datasetBuilder, Preprocessor<K,V> basePreprocessor) Fits preprocessor.

Uses of LearningEnvironmentBuilder in org.apache.ignite.ml.recommendation

Methods in org.apache.ignite.ml.recommendation with parameters of type LearningEnvironmentBuilder

Modifier and Type	Method and Description
RecommendationTrainer	RecommendationTrainer.withLearningEnvironmentBuilder(LearningEnvironmentBuilder environmentBuilder) Set up learning environment builder.

Uses of LearningEnvironmentBuilder in org.apache.ignite.ml.selection.cv

Fields in org.apache.ignite.ml.selection.cv declared as LearningEnvironmentBuilder

Modifier and Type	Field and Description
protected LearningEnvironmentBuilder	AbstractCrossValidation.envBuilder Learning environment builder.

Methods in org.apache.ignite.ml.selection.cv with parameters of type LearningEnvironmentBuilder

Modifier and Type	Method and Description
AbstractCrossValidation<M,L,K,V>	AbstractCrossValidation.withEnvironmentBuilder(LearningEnvironmentBuilder envBuilder) Changes learning Environment.

Uses of LearningEnvironmentBuilder in org.apache.ignite.ml.trainers

Fields in org.apache.ignite.ml.trainers declared as LearningEnvironmentBuilder

Modifier and Type	Field and Description
protected LearningEnvironmentBuilder	DatasetTrainer.envBuilder Learning environment builder.

Methods in org.apache.ignite.ml.trainers with parameters of type LearningEnvironmentBuilder

Modifier and Type	Method and Description
DatasetTrainer<M,L>	DatasetTrainer.withEnvironmentBuilder(LearningEnvironmentBuilder envBuilder) Changes learning Environment.

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

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

Modifier and Type	Method and Description
DecisionTreeClassificationTrainer	DecisionTreeClassificationTrainer.withEnvironmentBuilder(LearningEnvironmentBuilder envBuilder) Changes learning Environment.
DecisionTree<T>	DecisionTree.withEnvironmentBuilder(LearningEnvironmentBuilder envBuilder) Changes learning Environment.
DecisionTreeRegressionTrainer	DecisionTreeRegressionTrainer.withEnvironmentBuilder(LearningEnvironmentBuilder envBuilder) Changes learning Environment.

Uses of LearningEnvironmentBuilder in org.apache.ignite.ml.tree.boosting

Methods in org.apache.ignite.ml.tree.boosting with parameters of type LearningEnvironmentBuilder

Modifier and Type	Method and Description
GDBRegressionOnTreesTrainer	GDBRegressionOnTreesTrainer.withEnvironmentBuilder(LearningEnvironmentBuilder envBuilder) Changes learning Environment.
GDBBinaryClassifierOnTreesTrainer	GDBBinaryClassifierOnTreesTrainer.withEnvironmentBuilder(LearningEnvironmentBuilder envBuilder) Changes learning Environment.

Uses of LearningEnvironmentBuilder in org.apache.ignite.ml.tree.randomforest

Methods in org.apache.ignite.ml.tree.randomforest with parameters of type LearningEnvironmentBuilder

Modifier and Type	Method and Description
RandomForestClassifierTrainer	RandomForestClassifierTrainer.withEnvironmentBuilder(LearningEnvironmentBuilder envBuilder) Changes learning Environment.