​Because the observations in the data set don't differ much between them​. To be more specific, the data set consists of a congeneric series of organic molecules and the ebservation is their binding strength to a target protein. The idea was to train predictors that can predict the binding strenght of new molecules that belong to the same congeneric series. Therefore special care is taken to apply the predictors to the right domain of applicability. According to the literature, the same strategy has been followed in the past several times. The novelty of my approach stems from other factors that are irrelevant to this thread.