1. A machine learning system comprising: an input arranged to access at least one relational database; at least one store holding a model of a probabilistic relational database formed from the at least one relational database, the model comprising a relational database schema comprising at least one relation schema which itself comprises a relation name and a plurality of attributes at least some of which are probabilistic attributes; the at least one store holding the model such that it comprises a plurality of relational algebra instructions at least some of which are arranged to query data from the relational database and at least some of which comprise factor operations each of which specifies a mapping to a probability distribution; a processor arranged to translate the model into a factor graph data structure using specified semantics being rules stored at the memory; an inference engine arranged to carry out inference according to the factor graph data structure by using the data in the relational database and updating values of the probabilistic attributes.