## Uses of Class
org.apache.ignite.ml.composition.boosting.GDBTrainer.GDBModel

- Packages that use GDBTrainer.GDBModel
  Package | Description
  --- | ---
  org.apache.ignite.ml.composition.boosting | Contains Gradient Boosting regression and classification abstract classes allowing regressor type selecting in child classes.
  org.apache.ignite.ml.tree.boosting | Contains implementation of gradient boosting on trees.

- - ### Uses of GDBTrainer.GDBModel in org.apache.ignite.ml.composition.boosting

    Methods in org.apache.ignite.ml.composition.boosting with parameters of type GDBTrainer.GDBModel
    Modifier and Type | Method and Description
    --- | ---
    `protected @NotNull List<IgniteModel<Vector,Double>>` | GDBLearningStrategy.`initLearningState(GDBTrainer.GDBModel mdlToUpdate)` Restores state of already learned model if can and sets learning parameters according to this state.
    `<K,V> List<IgniteModel<Vector,Double>>` | GDBLearningStrategy.`update(GDBTrainer.GDBModel mdlToUpdate, 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.

  - ### Uses of GDBTrainer.GDBModel in org.apache.ignite.ml.tree.boosting

    Methods in org.apache.ignite.ml.tree.boosting with parameters of type GDBTrainer.GDBModel
    Modifier and Type | Method and Description
    --- | ---
    `<K,V> List<IgniteModel<Vector,Double>>` | GDBOnTreesLearningStrategy.`update(GDBTrainer.GDBModel mdlToUpdate, DatasetBuilder<K,V> datasetBuilder, Preprocessor<K,V> vectorizer)` 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.

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Release Date | : October 15 2020