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

Packages that use BaggedModel

Package	Description
org.apache.ignite.ml.composition.bagging	Contains bootstrap aggregation (bagging) trainer allowing to combine some other trainers and return a bagged version of them.

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.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> 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.