Optimizing Ensemble Weights and Hyperparameters of Machine Learning Models for Regression Problems

14 Aug 2019 Mohsen Shahhosseini Guiping Hu Hieu Pham

Aggregating multiple learners through an ensemble of models aim to make better predictions by capturing the underlying distribution of the data more accurately. Different ensembling methods, such as bagging, boosting, and stacking/blending, have been studied and adopted extensively in research and practice... (read more)

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