DOME: recommendations for supervised machine learning validation in biology - Nature Methods

The recommendations cover four major aspects of supervised ML according to the DOME acronym. The key points and rationale for each aspect of DOME are described below and summarized in Table 1. Box 1 provides an actionable checklist (with the recommendations codified as questions), which we suggest authors use as a guide when reporting ML-based methods in manuscripts. State-of-the-art ML models are often capable of memorizing all the variation in training data. Such models when evaluated on data that they were exposed to during training would create the illusion of mastering the task at hand.