Towards Structural Logistic Regression: Combining Relational and Statistical Learning

Inductive logic programming (ILP) techniques are useful for analyzing data in multi-table relational databases. Learned rules can potentially discover relationships that are not obvious in ``flattened"" data. Statistical learners, on the other hand, are generally not constructed to search relational data, they expect to be presented with a single table containing a set of feature candidates. However, statistical learners often yield more accurate models than the logical forms of ILP, and can...