Several different QSAR techniques have been applied to sweetness data for 50 sulfamates, RNHSO3-Na (21 sweet, 20 sweet-bitter, and 9 bitter). Stepwise discriminant analysis has been used to separate the 50 molecules into 3 classes, sweet, sweet-bitter, and bitter. Cluster analysis using two principal components can clearly distinguish between the sweet and sweet-bitter molecules but not between all three classes. Regression analysis has been used to develop equations for parameters fitting to log(RS) (RS, relative sweetness). The genetic algorithm method has been used to select parameters, and high correlations between log(RS) and a range of parameters have been achieved. Molecular field analysis followed by selection of relevant grid points by genetic algorithm yielded a result in which six grid points gave a high correlation coefficient (r(2) = 0.958, XVr(2) = 0.902).