## Uses of Class
org.apache.ignite.ml.composition.combinators.sequential.ModelsSequentialComposition

- Packages that use ModelsSequentialComposition
  Package | Description
  --- | ---
  org.apache.ignite.ml.composition.combinators.sequential | Contains sequential combinators of trainers and models.

- - ### Uses of ModelsSequentialComposition in org.apache.ignite.ml.composition.combinators.sequential

    Methods in org.apache.ignite.ml.composition.combinators.sequential that return ModelsSequentialComposition
    Modifier and Type | Method and Description
    --- | ---
    `<K,V> ModelsSequentialComposition<I,O1,O2>` | TrainersSequentialComposition.`fitWithInitializedDeployingContext(DatasetBuilder<K,V> datasetBuilder, Preprocessor<K,V> preprocessor)` Trains model based on the specified data.
    `static <I,O> ModelsSequentialComposition<I,O,O>` | ModelsSequentialComposition.`ofSame(List<? extends IgniteModel<I,O>> lst, IgniteFunction<O,I> output2Input)` Get sequential composition of submodels with same type.
    `<K,V> ModelsSequentialComposition<I,O1,O2>` | TrainersSequentialComposition.`update(ModelsSequentialComposition<I,O1,O2> mdl, DatasetBuilder<K,V> datasetBuilder, Preprocessor<K,V> preprocessor)` Gets state of model in arguments, compare it with training parameters of trainer and if they are fit then trainer updates model in according to new data and return new model.
    `protected <K,V> ModelsSequentialComposition<I,O1,O2>` | TrainersSequentialComposition.`updateModel(ModelsSequentialComposition<I,O1,O2> mdl, DatasetBuilder<K,V> datasetBuilder, Preprocessor<K,V> preprocessor)` This method is never called, instead of constructing logic of update from `DatasetTrainer.isUpdateable(IgniteModel)` and `DatasetTrainer.updateModel(IgniteModel, DatasetBuilder, Preprocessor)` in this class we explicitly override update method.

    Methods in org.apache.ignite.ml.composition.combinators.sequential with parameters of type ModelsSequentialComposition
    Modifier and Type | Method and Description
    --- | ---
    `boolean` | TrainersSequentialComposition.`isUpdateable(ModelsSequentialComposition<I,O1,O2> mdl)` This method is never called, instead of constructing logic of update from `DatasetTrainer.isUpdateable(M)` and `DatasetTrainer.updateModel(M, org.apache.ignite.ml.dataset.DatasetBuilder<K, V>, org.apache.ignite.ml.preprocessing.Preprocessor<K, V>)` in this class we explicitly override update method.
    `<K,V> ModelsSequentialComposition<I,O1,O2>` | TrainersSequentialComposition.`update(ModelsSequentialComposition<I,O1,O2> mdl, DatasetBuilder<K,V> datasetBuilder, Preprocessor<K,V> preprocessor)` Gets state of model in arguments, compare it with training parameters of trainer and if they are fit then trainer updates model in according to new data and return new model.
    `protected <K,V> ModelsSequentialComposition<I,O1,O2>` | TrainersSequentialComposition.`updateModel(ModelsSequentialComposition<I,O1,O2> mdl, DatasetBuilder<K,V> datasetBuilder, Preprocessor<K,V> preprocessor)` This method is never called, instead of constructing logic of update from `DatasetTrainer.isUpdateable(IgniteModel)` and `DatasetTrainer.updateModel(IgniteModel, DatasetBuilder, Preprocessor)` in this class we explicitly override update method.

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Release Date | : April 20 2022