We describe a case study in tit(', application of symbolic machinc learning techniques for the discow;ry of linguistic rules and categories. A supervised rule induction algor...
When comparing inductive logic programming (ILP) and attribute-value learning techniques, there is a trade-off between expressive power and efficiency. Inductive logic programming ...
Hendrik Blockeel, Luc De Raedt, Nico Jacobs, Bart ...
The article describes a method combining two widely-used empirical approaches to learning from examples: rule induction and instance-based learning. In our algorithm (RIONA) decisi...
A central issue in logical concept induction is the prospect of inconsistency. This problem may arise due to noise in the training data, or because the target concept does not fit...
Regularized Least Squares (RLS) algorithms have the ability to avoid over-fitting problems and to express solutions as kernel expansions. However, we observe that the current RLS ...