## 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 convergence 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.compound | Contains Compound naive Bayes classifier.
  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.finalization | Contains vector finalization preprocessor.
  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.
    `GDBTrainer` | GDBTrainer.`withEnvironmentBuilder(LearningEnvironmentBuilder envBuilder)` Changes learning Environment.
    `GDBLearningStrategy` | GDBLearningStrategy.`withEnvironmentBuilder(LearningEnvironmentBuilder envBuilder)` Sets learning environment.
    `GDBBinaryClassifierOnTreesTrainer` | GDBBinaryClassifierTrainer.`withEnvironmentBuilder(LearningEnvironmentBuilder envBuilder)` Changes learning Environment.
    `GDBRegressionTrainer` | GDBRegressionTrainer.`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 deployingCtx)` 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` | LearningEnvironmentBuilder.`withDataTtl(long dataTtl)` Specify partition data time-to-live in seconds (-1 for an infinite lifetime).
    `LearningEnvironmentBuilder` | DefaultLearningEnvironmentBuilder.`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` | LearningEnvironmentBuilder.`withRandomDependency(IgniteFunction<Integer,Random> rngSupplier)` Specify dependency (partition -> random numbers generator).
    `LearningEnvironmentBuilder` | DefaultLearningEnvironmentBuilder.`withRandomDependency(IgniteFunction<Integer,Random> rngSupplier)` Specify dependency (partition -> random numbers generator).
    `default LearningEnvironmentBuilder` | LearningEnvironmentBuilder.`withRNGSeed(long seed)` Specify seed for random number generator.
    `LearningEnvironmentBuilder` | LearningEnvironmentBuilder.`withRNGSeedDependency(IgniteFunction<Integer,Long> seed)` Specify dependency (partition -> seed for random number generator).
    `LearningEnvironmentBuilder` | DefaultLearningEnvironmentBuilder.`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> @Nullable 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.compound

    Methods in org.apache.ignite.ml.naivebayes.compound with parameters of type LearningEnvironmentBuilder
    Modifier and Type | Method and Description
    --- | ---
    `CompoundNaiveBayesTrainer` | CompoundNaiveBayesTrainer.`withEnvironmentBuilder(LearningEnvironmentBuilder envBuilder)` Changes learning Environment.

  - ### 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.finalization

    Methods in org.apache.ignite.ml.preprocessing.finalization with parameters of type LearningEnvironmentBuilder
    Modifier and Type | Method and Description
    --- | ---
    `VectorFinalizationPreprocessor<K,V>` | VectorFinalizationTrainer.`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,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
    --- | ---
    `DecisionTreeRegressionTrainer` | DecisionTreeRegressionTrainer.`withEnvironmentBuilder(LearningEnvironmentBuilder envBuilder)` Changes learning Environment.
    `DecisionTreeTrainer<T>` | DecisionTreeTrainer.`withEnvironmentBuilder(LearningEnvironmentBuilder envBuilder)` Changes learning Environment.
    `DecisionTreeClassificationTrainer` | DecisionTreeClassificationTrainer.`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.

2022 Copyright © Apache Software Foundation
| Follow @ApacheIgnite
Ignite Database and Caching Platform | : ver. 2.13.0
Release Date | : April 20 2022