## Uses of Class
org.apache.ignite.ml.composition.bagging.BaggedModel

- Packages that use BaggedModel
  Package | Description
  --- | ---
  org.apache.ignite.ml.composition.bagging |

- - ### Uses of BaggedModel in org.apache.ignite.ml.composition.bagging

    Methods in org.apache.ignite.ml.composition.bagging that return BaggedModel
    Modifier and Type | Method and Description
    --- | ---
    `<K,V> BaggedModel` | BaggedTrainer.`fitWithInitializedDeployingContext(DatasetBuilder<K,V> datasetBuilder, Preprocessor<K,V> preprocessor)` Trains model based on the specified data.
    `<K,V> BaggedModel` | BaggedTrainer.`update(BaggedModel 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> BaggedModel` | BaggedTrainer.`updateModel(BaggedModel mdl, DatasetBuilder<K,V> datasetBuilder, Preprocessor<K,V> preprocessor)` 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.

    Methods in org.apache.ignite.ml.composition.bagging with parameters of type BaggedModel
    Modifier and Type | Method and Description
    --- | ---
    `boolean` | BaggedTrainer.`isUpdateable(BaggedModel mdl)` This method is never called, instead of constructing logic of update from `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> BaggedModel` | BaggedTrainer.`update(BaggedModel 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> BaggedModel` | BaggedTrainer.`updateModel(BaggedModel mdl, DatasetBuilder<K,V> datasetBuilder, Preprocessor<K,V> preprocessor)` 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.

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Release Date | : September 11 2021