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Gradient boosting models have gained immense popularity over the past decade. With dozens of academic papers written about them, they have become a staple solution for ML models in a variety of fields, and have been implemented by multiple leading companies in the field of machine learning. As with all other ML models, if not tuned correctly boosting models can overfit on the training data and thus perform poorly when predicting using unseen data.
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