Abstract: In a rule generation apparatus, a rule generation unit generates a rule group for dividing a training example into a plurality of clusters related to target values using a rule base model so that a “first constraint” is satisfied. The training example includes at least one real example and at least one synthetic example. Each of the real and the synthetic examples includes a feature value vector of which vector elements are one or a plurality of feature values corresponding to feature parameters different from each other, and a target value. The feature value and the target value included in each of the real examples are measured values, while each of the synthetic examples is an example formed based on the real example. The “first constraint” includes a constraint that each of the clusters includes at least N (N is a natural number) real example.