/efficient-multiclass-classification

Duet is a scikit-learn classifier for resource-efficient multiclass classification that incorporates the advantages of bagging and boosting decision-tree-based ensemble methods (DTEMs) by using two classifiers instead of a monolithic one. A simple bagging model is trained using the entire training dataset and is responsible for capturing the easier concepts. Then, a boosting model is trained using only a fraction of the dataset representing the concepts the bagging model finds hard.

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