Ensembles
Heterogeneous AdaBoost Classifier

HeteroAdaBoostClassifier

Similar to AdaBoostClassifier, but instead of multiple copies of the same model, it can work with different base models.

Parameters

  • base_models(list[Model]) → The list of classifier models.

  • n_classes(int) → The number of classes for the classifier.

  • seed(int, Default:0) → Random number generator seed for reproducibility.

Example Usage

We can create an instance and deploy AdaBoostClassifier model like this.

import turboml as tb
model = tb.HeteroAdaBoostClassifier(n_classes=2, base_models = [tb.HoeffdingTreeClassifier(n_classes=2), tb.AMFClassifier(n_classes=2)])
Heterogeneous Leveraging Bagging ClassifierLLAMA Embedding