• Corpus ID: 234742642

Cross-Cluster Weighted Forests

@article{Ramchandran2021CrossClusterWF,
  title={Cross-Cluster Weighted Forests},
  author={Maya Ramchandran and Rajarshi Mukherjee and Giovanni Parmigiani},
  journal={ArXiv},
  year={2021},
  volume={abs/2105.07610}
}
Adapting machine learning algorithms to better handle the presence of natural clustering or batch effects within training datasets is imperative across a wide variety of biological applications. This article considers the effect of ensembling Random Forest learners trained on clusters within a single dataset with heterogeneity in the distribution of the features. We find that constructing ensembles of forests trained on clusters determined by algorithms such as k-means results in significant… 

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