org.apache.ignite.ml.dataset

## Class DatasetFactory

- java.lang.Object
- - org.apache.ignite.ml.dataset.DatasetFactory

-     public class DatasetFactory
      extends Object

  Factory providing a client facing API that allows to construct basic and the most frequently used types of dataset.

  Dataset construction is based on three major concepts: a partition `upstream`, `context` and `data`. A partition `upstream` is a data source, which assumed to be available all the time regardless node failures and rebalancing events. A partition `context` is a part of a partition maintained during the whole computation process and stored in a reliable storage so that a `context` is staying available and consistent regardless node failures and rebalancing events as well as an `upstream`. A partition `data` is a part of partition maintained during a computation process in unreliable local storage such as heap, off-heap or GPU memory on the node where current computation is performed, so that partition `data` can be lost as result of node failure or rebalancing, but it can be restored from an `upstream` and a partition `context`.

  A partition `context` and `data` are built on top of an `upstream` by using specified builders: `PartitionContextBuilder` and `PartitionDataBuilder` correspondingly. To build a generic dataset the following approach is used: ``Dataset<C, D> dataset = DatasetFactory.create( ignite, cache, partitionContextBuilder, partitionDataBuilder );``

  As well as the generic building method `create` this factory provides methods that allow to create a specific dataset types such as method `createSimpleDataset` to create `SimpleDataset` and method `createSimpleLabeledDataset` to create `SimpleLabeledDataset`.

  See Also:
    `Dataset`, `PartitionContextBuilder`, `PartitionDataBuilder`

- - ### Constructor Summary

    Constructors
    Constructor and Description
    `DatasetFactory()`

  - ### Method Summary

    All Methods Static Methods Concrete Methods
    Modifier and Type | Method and Description
    --- | ---
    `static <K,V,C extends Serializable,D extends AutoCloseable> Dataset<C,D>` | `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>` | `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>` | `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>` | `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>` | `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>` | `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>` | `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>` | `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>` | `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,CO extends Serializable> SimpleDataset<EmptyContext>` | `createSimpleDataset(Ignite ignite, IgniteCache<K,V> upstreamCache, 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>` | `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>` | `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>` | `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>` | `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>` | `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>` | `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>` | `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>` | `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`.

    - ### Methods inherited from class java.lang.Object

      `clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

- - ### Constructor Detail

    - #### DatasetFactory

          public DatasetFactory()

  - ### Method Detail

    - #### create

          public static <K,V,C extends Serializable,D extends AutoCloseable> Dataset<C,D> 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`. This is the generic methods that allows to create any Ignite Cache based datasets with any desired partition `context` and `data`.
      Type Parameters:
        `K` - Type of a key in `upstream` data.
        `V` - ype of a value in `upstream` data.
        `C` - Type of a partition `context`.
        `D` - Type of a partition `data`.
      Parameters:
        `envBuilder` - Learning environment builder.
        `datasetBuilder` - Dataset builder.
        `partCtxBuilder` - Partition `context` builder.
        `partDataBuilder` - Partition `data` builder.
        `environment` - Local learning environment.
      Returns:
        Dataset.

    - #### create

          public static <K,V,C extends Serializable,D extends AutoCloseable> Dataset<C,D> 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`. This is the generic methods that allows to create any Ignite Cache based datasets with any desired partition `context` and `data`.
      Type Parameters:
        `K` - Type of a key in `upstream` data.
        `V` - ype of a value in `upstream` data.
        `C` - Type of a partition `context`.
        `D` - Type of a partition `data`.
      Parameters:
        `datasetBuilder` - Dataset builder.
        `partCtxBuilder` - Partition `context` builder.
        `partDataBuilder` - Partition `data` builder.
      Returns:
        Dataset.

    - #### create

          public static <K,V,C extends Serializable,D extends AutoCloseable> Dataset<C,D> 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`. This is the generic methods that allows to create any Ignite Cache based datasets with any desired partition `context` and `data`.
      Type Parameters:
        `K` - Type of a key in `upstream` data.
        `V` - Type of a value in `upstream` data.
        `C` - Type of a partition `context`.
        `D` - Type of a partition `data`.
      Parameters:
        `ignite` - Ignite instance.
        `upstreamCache` - Ignite Cache with `upstream` data.
        `envBuilder` - Learning environment builder.
        `partCtxBuilder` - Partition `context` builder.
        `partDataBuilder` - Partition `data` builder.
        `environment` - Local learning environment.
      Returns:
        Dataset.

    - #### create

          public static <K,V,C extends Serializable,D extends AutoCloseable> Dataset<C,D> 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`. This is the generic methods that allows to create any Ignite Cache based datasets with any desired partition `context` and `data`.
      Type Parameters:
        `K` - Type of a key in `upstream` data.
        `V` - Type of a value in `upstream` data.
        `C` - Type of a partition `context`.
        `D` - Type of a partition `data`.
      Parameters:
        `ignite` - Ignite instance.
        `upstreamCache` - Ignite Cache with `upstream` data.
        `partCtxBuilder` - Partition `context` builder.
        `partDataBuilder` - Partition `data` builder.
      Returns:
        Dataset.

    - #### createSimpleDataset

          public static <K,V,C extends Serializable,CO extends Serializable> SimpleDataset<C> 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`. This methods determines partition `data` to be `SimpleDatasetData`, but allows to use any desired type of partition `context`.
      Type Parameters:
        `K` - Type of a key in `upstream` data.
        `V` - Type of a value in `upstream` data.
        `C` - Type of a partition `context`.
      Parameters:
        `datasetBuilder` - Dataset builder.
        `envBuilder` - Learning environment builder.
        `partCtxBuilder` - Partition `context` builder.
        `featureExtractor` - Feature extractor used to extract features and build `SimpleDatasetData`.
      Returns:
        Dataset.

    - #### createSimpleDataset

          public static <K,V,C extends Serializable,CO extends Serializable> SimpleDataset<C> 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`. This methods determines partition `data` to be `SimpleDatasetData`, but allows to use any desired type of partition `context`.
      Type Parameters:
        `K` - Type of a key in `upstream` data.
        `V` - Type of a value in `upstream` data.
        `C` - Type of a partition `context`.
      Parameters:
        `ignite` - Ignite instance.
        `upstreamCache` - Ignite Cache with `upstream` data.
        `envBuilder` - Learning environment builder.
        `partCtxBuilder` - Partition `context` builder.
        `featureExtractor` - Feature extractor used to extract features and build `SimpleDatasetData`.
      Returns:
        Dataset.

    - #### createSimpleLabeledDataset

          public static <K,V,C extends Serializable,CO extends Serializable> SimpleLabeledDataset<C> 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`. This method determines partition `data` to be `SimpleLabeledDatasetData`, but allows to use any desired type of partition `context`.
      Type Parameters:
        `K` - Type of a key in `upstream` data.
        `V` - Type of a value in `upstream` data.
        `C` - Type of a partition `context`.
      Parameters:
        `datasetBuilder` - Dataset builder.
        `envBuilder` - Learning environment builder.
        `partCtxBuilder` - Partition `context` builder.
        `vectorizer` - Upstream vectorizer used to extract features and labels and build `SimpleLabeledDatasetData`.
      Returns:
        Dataset.

    - #### createSimpleLabeledDataset

          public static <K,V,C extends Serializable,CO extends Serializable> SimpleLabeledDataset<C> 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`. This method determines partition `data` to be `SimpleLabeledDatasetData`, but allows to use any desired type of partition `context`.
      Type Parameters:
        `K` - Type of a key in `upstream` data.
        `V` - Type of a value in `upstream` data.
        `C` - Type of a partition `context`.
      Parameters:
        `ignite` - Ignite instance.
        `upstreamCache` - Ignite Cache with `upstream` data.
        `envBuilder` - Learning environment builder.
        `partCtxBuilder` - Partition `context` builder.
        `vectorizer` - Upstream vectorizer used to extract features and labels and build `SimpleLabeledDatasetData`.
      Returns:
        Dataset.

    - #### createSimpleDataset

          public static <K,V,CO extends Serializable> SimpleDataset<EmptyContext> createSimpleDataset(DatasetBuilder<K,V> datasetBuilder,
                                                                                                      LearningEnvironmentBuilder envBuilder,
                                                                                                      Preprocessor<K,V> featureExtractor)

      Creates a new instance of distributed `SimpleDataset` using the specified `featureExtractor`. This methods determines partition `context` to be `EmptyContext` and partition `data` to be `SimpleDatasetData`.
      Type Parameters:
        `K` - Type of a key in `upstream` data.
        `V` - Type of a value in `upstream` data.
      Parameters:
        `datasetBuilder` - Dataset builder.
        `envBuilder` - Learning environment builder.
        `featureExtractor` - Feature extractor used to extract features and build `SimpleDatasetData`.
      Returns:
        Dataset.

    - #### createSimpleDataset

          public static <K,V,CO extends Serializable> SimpleDataset<EmptyContext> createSimpleDataset(Ignite ignite,
                                                                                                      IgniteCache<K,V> upstreamCache,
                                                                                                      LearningEnvironmentBuilder envBuilder,
                                                                                                      Preprocessor<K,V> featureExtractor)

      Creates a new instance of distributed `SimpleDataset` using the specified `featureExtractor`. This methods determines partition `context` to be `EmptyContext` and partition `data` to be `SimpleDatasetData`.
      Type Parameters:
        `K` - Type of a key in `upstream` data.
        `V` - Type of a value in `upstream` data.
      Parameters:
        `ignite` - Ignite instance.
        `upstreamCache` - Ignite Cache with `upstream` data.
        `envBuilder` - Learning environment builder.
        `featureExtractor` - Feature extractor used to extract features and build `SimpleDatasetData`.
      Returns:
        Dataset.

    - #### createSimpleDataset

          public static <K,V,CO extends Serializable> SimpleDataset<EmptyContext> createSimpleDataset(Ignite ignite,
                                                                                                      IgniteCache<K,V> upstreamCache,
                                                                                                      Preprocessor<K,V> featureExtractor)

      Creates a new instance of distributed `SimpleDataset` using the specified `featureExtractor`. This methods determines partition `context` to be `EmptyContext` and partition `data` to be `SimpleDatasetData`.
      Type Parameters:
        `K` - Type of a key in `upstream` data.
        `V` - Type of a value in `upstream` data.
      Parameters:
        `ignite` - Ignite instance.
        `upstreamCache` - Ignite Cache with `upstream` data.
        `featureExtractor` - Feature extractor used to extract features and build `SimpleDatasetData`.
      Returns:
        Dataset.

    - #### createSimpleLabeledDataset

          public static <K,V,CO extends Serializable> SimpleLabeledDataset<EmptyContext> createSimpleLabeledDataset(DatasetBuilder<K,V> datasetBuilder,
                                                                                                                    LearningEnvironmentBuilder envBuilder,
                                                                                                                    Preprocessor<K,V> vectorizer)

      Creates a new instance of distributed `SimpleLabeledDataset` using the specified `featureExtractor` and `lbExtractor`. This methods determines partition `context` to be `EmptyContext` and partition `data` to be `SimpleLabeledDatasetData`.
      Type Parameters:
        `K` - Type of a key in `upstream` data.
        `V` - Type of a value in `upstream` data.
      Parameters:
        `datasetBuilder` - Dataset builder.
        `envBuilder` - Learning environment builder.
        `vectorizer` - Upstream vectorizer used to extract features and labels and build `SimpleLabeledDatasetData`.
      Returns:
        Dataset.

    - #### createSimpleLabeledDataset

          public static <K,V,CO extends Serializable> SimpleLabeledDataset<EmptyContext> 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`. This methods determines partition `context` to be `EmptyContext` and partition `data` to be `SimpleLabeledDatasetData`.
      Type Parameters:
        `K` - Type of a key in `upstream` data.
        `V` - Type of a value in `upstream` data.
      Parameters:
        `ignite` - Ignite instance.
        `upstreamCache` - Ignite Cache with `upstream` data.
        `envBuilder` - Learning environment builder.
        `vectorizer` - Upstream vectorizer used to extract features and labels and build `SimpleLabeledDatasetData`.
      Returns:
        Dataset.

    - #### create

          public static <K,V,C extends Serializable,D extends AutoCloseable> Dataset<C,D> 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`. This is the generic methods that allows to create any Ignite Cache based datasets with any desired partition `context` and `data`.
      Type Parameters:
        `K` - Type of a key in `upstream` data.
        `V` - Type of a value in `upstream` data.
        `C` - Type of a partition `context`.
        `D` - Type of a partition `data`.
      Parameters:
        `upstreamMap` - `Map` with `upstream` data.
        `partitions` - Number of partitions `upstream` `Map` will be divided on.
        `partCtxBuilder` - Partition `context` builder.
        `envBuilder` - Learning environment builder.
        `partDataBuilder` - Partition `data` builder.
        `environment` - Local learning environment.
      Returns:
        Dataset.

    - #### createSimpleDataset

          public static <K,V,C extends Serializable,CO extends Serializable> SimpleDataset<C> 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`. This methods determines partition `data` to be `SimpleDatasetData`, but allows to use any desired type of partition `context`.
      Type Parameters:
        `K` - Type of a key in `upstream` data.
        `V` - Type of a value in `upstream` data.
        `C` - Type of a partition `context`.
      Parameters:
        `upstreamMap` - `Map` with `upstream` data.
        `partitions` - Number of partitions `upstream` `Map` will be divided on.
        `envBuilder` - Learning environment builder.
        `partCtxBuilder` - Partition `context` builder.
        `featureExtractor` - Feature extractor used to extract features and build `SimpleDatasetData`.
      Returns:
        Dataset.

    - #### createSimpleLabeledDataset

          public static <K,V,C extends Serializable,CO extends Serializable> SimpleLabeledDataset<C> 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`. This method determines partition `data` to be `SimpleLabeledDatasetData`, but allows to use any desired type of partition `context`.
      Type Parameters:
        `K` - Type of a key in `upstream` data.
        `V` - Type of a value in `upstream` data.
        `C` - Type of a partition `context`.
      Parameters:
        `upstreamMap` - `Map` with `upstream` data.
        `partitions` - Number of partitions `upstream` `Map` will be divided on.
        `envBuilder` - Learning environment builder.
        `partCtxBuilder` - Partition `context` builder.
        `vectorizer` - Upstream vectorizer used to extract features and labels and build `SimpleLabeledDatasetData`.
      Returns:
        Dataset.

    - #### createSimpleDataset

          public static <K,V,CO extends Serializable> SimpleDataset<EmptyContext> createSimpleDataset(Map<K,V> upstreamMap,
                                                                                                      int partitions,
                                                                                                      LearningEnvironmentBuilder envBuilder,
                                                                                                      Preprocessor<K,V> featureExtractor)

      Creates a new instance of local `SimpleDataset` using the specified `featureExtractor`. This methods determines partition `context` to be `EmptyContext` and partition `data` to be `SimpleDatasetData`.
      Type Parameters:
        `K` - Type of a key in `upstream` data.
        `V` - Type of a value in `upstream` data.
      Parameters:
        `upstreamMap` - `Map` with `upstream` data.
        `partitions` - Number of partitions `upstream` `Map` will be divided on.
        `envBuilder` - Learning environment builder.
        `featureExtractor` - Feature extractor used to extract features and build `SimpleDatasetData`.
      Returns:
        Dataset.

    - #### createSimpleLabeledDataset

          public static <K,V,CO extends Serializable> SimpleLabeledDataset<EmptyContext> 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`. This methods determines partition `context` to be `EmptyContext` and partition `data` to be `SimpleLabeledDatasetData`.
      Type Parameters:
        `K` - Type of a key in `upstream` data.
        `V` - Type of a value in `upstream` data.
      Parameters:
        `upstreamMap` - `Map` with `upstream` data.
        `partitions` - Number of partitions `upstream` `Map` will be divided on.
        `envBuilder` - Learning environment builder.
        `vectorizer` - Upstream vectorizer used to extract features and labels and build `SimpleLabeledDatasetData`.
      Returns:
        Dataset.

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Ignite Database and Caching Platform | : ver. 2.12.0
Release Date | : January 10 2022