Hi all, I have a slightly off-topic question. I'm trying to train a neural network on a dataset of small molecules and their melting points. I did get a not-so-bad accuracy with Morgan fingerprints, but I've realised that regardless of FP radius and bitvector length, several dozen molecules have the same fingerprints but wildly different melting points. I am pretty sure this is a "solved problem" so I don't want to reinvent the wheel. What is the recommended/usual way of dealing with this? Thanks, Michal
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