Comparing ML models in small molecule drug discovery

To start the post I'll share a photo that I took in 2012 of incense sticks at the Truc Lam pagoda near Da Lat. Not long after taking this photo I lost a lens cap (although thankfully not the lens) riding a luge through a forest and would later visit a cricket farm (this was particularly welcome because I had developed a taste for fried crickets during a visit to Cambodia in 2005). I’ll be reviewing A2025 (Practically Significant Method Comparison Protocols for Machine Learning in Small Molecule Drug Discovery) in this post. I consider the issues addressed by the authors to be extremely important and I think that the credibility of the Machine Learning (ML) field would be greatly enhanced if Editors declared words like 'outperform' to be verboten in manuscripts submitted to their journals. However, I will make a couple of criticisms of the study. First, ML modellers need to properly account for the number of adjustable parameters used to fit training data (the S2006 study goes further…