Harmonization of supervised machine learning practices for efficient source attribution of Listeria monocytogenes based on genomic data.

In addition to recommendations about machine learning practices for L. monocytogenes source attribution based on genomic data, the present study also provides a freely available workflow to solve other balanced or unbalanced multiclass phenotypes from binary and categorical genomic profiles of other microorganisms without source code modifications.