In-silico methods for predicting the bioactivities or biomacromolecular targets of small organic compounds are of enormous importance to pharmaceutical, agrochemical, and cosmetics research. In particular, in recent years, machine learning has evolved into a key technology for bioactivity and target prediction. The limiting factor in the further development of the computational methods is the measured bioactivity data available for model development.