1. Method for sampling a database for obtaining the probably approximately n best hypotheses having the highest empirically utility of a group of potential hypotheses, comprising the steps of: a) generating all possible hypotheses based on specifications of a user as remaining hypotheses, b) checking whether enough data points were sampled so far to distinguish within the group of potential hypotheses all good looking hypotheses from bad looking hypotheses with sufficient confidence, c) if according to step b) enough data points were sampled so far then continue with step j) otherwise continue with step f), d) sampling one or more data points, e) calculating the utility of all the remaining hypotheses on the basis of the sampled data points, f) in the set of remaining hypotheses determining a set of good looking hypotheses by taking the n hypotheses that currently have the highest utility based on the data points sampled so far, whereas the other hypotheses are added to a set of bad looking hypotheses, g) checking each of the remaining hypotheses wherein i) if the currently considered hypothesis with sufficient probability is sufficiently good when compared to all bad looking hypotheses then outputting the currently considered hypothesis, removing the currently considered hypothesis from the set of remaining hypotheses and from the set of good looking hypotheses, decrementing the number of hypotheses still to be found and if the number of hypotheses still to be found is zero or the number of remaining hypotheses is equal to the number of hypotheses still to be found, then continue with step j), ii) if the currently considered hypotheses with sufficient probability is sufficiently bad when compared with all the good looking hypotheses then removing the currently considered hypothesis from the set of bad looking hypotheses from the set of remaining hypotheses and if the number of remaining hypotheses is equal to the number of hypotheses still to be found, then continue with step j), h) continue with step a), j) outputting to a user the n best hypotheses having the highest utility of all the remaining hypotheses.