BioinformaticsbioRxivPreprint
Unsupervised encoding selection through ensemble pruning for biomedical classification
Sebastian Spänig, Alexander Michel, Dominik Heider
The paper presents a workflow for unsupervised encoding selection and ensemble creation for peptide classification, demonstrating that Pareto frontier pruning and Decision Tree base models perform well across datasets.
DOI 10.1101/2022.02.06.479282