BioinformaticsbioRxivPreprint
Differential Compositional Variation FeatureSelection: A Machine Learning Framework with LogRatios for Compositional Metagenomic Data
Andrew L. Hinton, Peter J. Mucha
This paper introduces DiCoVarML, a machine learning framework for metagenomic data that uses log ratios to improve classification accuracy through differential compositional variation feature selection.