# Generalized Negative Correlation Learning for Deep Ensembling

@article{Buschjger2020GeneralizedNC, title={Generalized Negative Correlation Learning for Deep Ensembling}, author={Sebastian Buschj{\"a}ger and Lukas Pfahler and Katharina Morik}, journal={ArXiv}, year={2020}, volume={abs/2011.02952} }

Ensemble algorithms offer state of the art performance in many machine learning applications. A common explanation for their excellent performance is due to the bias-variance decomposition of the mean squared error which shows that the algorithm's error can be decomposed into its bias and variance. Both quantities are often opposed to each other and ensembles offer an effective way to manage them as they reduce the variance through a diverse set of base learners while keeping the bias low at…

## 10 Citations

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