org.apache.ignite.ml.util.generators

## Interface DataStreamGenerator

- All Known Implementing Classes:
    GaussianMixtureDataStream, RegressionDataStream, RingsDataStream, TwoSeparableClassesDataStream

      public interface DataStreamGenerator

  Provides general interface for generation of pseudorandom vectors according to shape defined by logic of specific data stream generator.

- - ### Field Summary

    Fields
    Modifier and Type | Field and Description
    --- | ---
    `static int` | `FILL_CACHE_BATCH_SIZE` Size of batch for `IgniteCache.putAll(Map)`.

  - ### Method Summary

    All Methods Instance Methods Abstract Methods Default Methods
    Modifier and Type | Method and Description
    --- | ---
    `default DatasetBuilder<Vector,Double>` | `asDatasetBuilder(int datasetSize, IgniteBiPredicate<Vector,Double> filter, int partitions)` Convert first N values from stream to `DatasetBuilder`.
    `default DatasetBuilder<Vector,Double>` | `asDatasetBuilder(int datasetSize, IgniteBiPredicate<Vector,Double> filter, int partitions, UpstreamTransformerBuilder upstreamTransformerBuilder)` Convert first N values from stream to `DatasetBuilder`.
    `default DatasetBuilder<Vector,Double>` | `asDatasetBuilder(int datasetSize, int partitions)` Convert first N values from stream to `DatasetBuilder`.
    `default Map<Vector,Double>` | `asMap(int datasetSize)` Convert first N values from stream to map.
    `default DataStreamGenerator` | `blur(RandomProducer rnd)` Apply pseudorandom noize to vectors without labels mapping.
    `default <K> void` | `fillCacheWithCustomKey(int datasetSize, IgniteCache<K,LabeledVector<Double>> cache, Function<LabeledVector<Double>,K> keyMapper)` Fills given cache with labeled vectors from this generator and user defined mapper from vectors to keys.
    `default void` | `fillCacheWithVecHashAsKey(int datasetSize, IgniteCache<Integer,LabeledVector<Double>> cache)` Fills given cache with labeled vectors from this generator as values and their hashcodes as keys.
    `default void` | `fillCacheWithVecUUIDAsKey(int datasetSize, IgniteCache<UUID,LabeledVector<Double>> cache)` Fills given cache with labeled vectors from this generator as values and random UUIDs as keys
    `Stream<LabeledVector<Double>>` | `labeled()`
    `default Stream<LabeledVector<Double>>` | `labeled(IgniteFunction<Vector,Double> classifier)`
    `default DataStreamGenerator` | `mapVectors(IgniteFunction<Vector,Vector> f)` Apply user defined mapper to vectors stream without labels hiding.
    `default Stream<Vector>` | `unlabeled()`

- - ### Field Detail

    - #### FILL_CACHE_BATCH_SIZE

          static final int FILL_CACHE_BATCH_SIZE

      Size of batch for `IgniteCache.putAll(Map)`.
      See Also:
        Constant Field Values

  - ### Method Detail

    - #### labeled

          Stream<LabeledVector<Double>> labeled()

      Returns:
        Stream of `LabeledVector` in according to dataset shape.

    - #### unlabeled

          default Stream<Vector> unlabeled()

      Returns:
        Stream of unlabeled `Vector` in according to dataset shape.

    - #### labeled

          default Stream<LabeledVector<Double>> labeled(IgniteFunction<Vector,Double> classifier)

      Parameters:
        `classifier` - User defined classifier for vectors stream.
      Returns:
        Stream of `LabeledVector` in according to dataset shape and user's classifier.

    - #### mapVectors

          default DataStreamGenerator mapVectors(IgniteFunction<Vector,Vector> f)

      Apply user defined mapper to vectors stream without labels hiding.
      Parameters:
        `f` - Mapper of vectors of data stream.
      Returns:
        Stream of mapped vectors.

    - #### blur

          default DataStreamGenerator blur(RandomProducer rnd)

      Apply pseudorandom noize to vectors without labels mapping. Such method can be useful in cases when vectors with different labels should be mixed between them on class bounds.
      Parameters:
        `rnd` - Generator of pseudorandom scalars modifying vector components with label saving.
      Returns:
        Stream of blurred vectors with same labels.

    - #### asMap

          default Map<Vector,Double> asMap(int datasetSize)

      Convert first N values from stream to map.
      Parameters:
        `datasetSize` - Dataset size.
      Returns:
        Map of vectors and labels.

    - #### asDatasetBuilder

          default DatasetBuilder<Vector,Double> asDatasetBuilder(int datasetSize,
                                                                 int partitions)

      Convert first N values from stream to `DatasetBuilder`.
      Parameters:
        `datasetSize` - Dataset size.
        `partitions` - Partitions count.
      Returns:
        Dataset builder.

    - #### asDatasetBuilder

          default DatasetBuilder<Vector,Double> asDatasetBuilder(int datasetSize,
                                                                 IgniteBiPredicate<Vector,Double> filter,
                                                                 int partitions)

      Convert first N values from stream to `DatasetBuilder`.
      Parameters:
        `datasetSize` - Dataset size.
        `filter` - Data filter.
        `partitions` - Partitions count.
      Returns:
        Dataset builder.

    - #### asDatasetBuilder

          default DatasetBuilder<Vector,Double> asDatasetBuilder(int datasetSize,
                                                                 IgniteBiPredicate<Vector,Double> filter,
                                                                 int partitions,
                                                                 UpstreamTransformerBuilder upstreamTransformerBuilder)

      Convert first N values from stream to `DatasetBuilder`.
      Parameters:
        `datasetSize` - Dataset size.
        `filter` - Data filter.
        `partitions` - Partitions count.
        `upstreamTransformerBuilder` - Upstream transformer builder.
      Returns:
        Dataset builder.

    - #### fillCacheWithCustomKey

          default <K> void fillCacheWithCustomKey(int datasetSize,
                                                  IgniteCache<K,LabeledVector<Double>> cache,
                                                  Function<LabeledVector<Double>,K> keyMapper)

      Fills given cache with labeled vectors from this generator and user defined mapper from vectors to keys.
      Type Parameters:
        `K` - Key type.
      Parameters:
        `datasetSize` - Rows count to put.
        `cache` - Cache.
        `keyMapper` - Mapping from vectors to keys.

    - #### fillCacheWithVecHashAsKey

          default void fillCacheWithVecHashAsKey(int datasetSize,
                                                 IgniteCache<Integer,LabeledVector<Double>> cache)

      Fills given cache with labeled vectors from this generator as values and their hashcodes as keys.
      Parameters:
        `datasetSize` - Rows count to put.
        `cache` - Cache.

    - #### fillCacheWithVecUUIDAsKey

          default void fillCacheWithVecUUIDAsKey(int datasetSize,
                                                 IgniteCache<UUID,LabeledVector<Double>> cache)

      Fills given cache with labeled vectors from this generator as values and random UUIDs as keys
      Parameters:
        `datasetSize` - Rows count to put.
        `cache` - Cache.

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