Learning to SMILE(S)
Table 1: Log-loss (± std) of each model for a given protein and representation.
['[EMPTY]', 'model', '5-HT1A', '5-HT2A', '5-HT7', 'H1', 'SERT']
First, simple n-gram models (SVM, RF) performance is close to hand crafted state of the art representation, which suggests that potentially any NLP classifier working on n-gram representation might be applicable. Maybe even more interestingly, current state of the art model for sentiment analysis - CNN - despite small dataset size, outperforms (however by a small margin) traditional models.