Three types of data modelling technique are applied retrospectively to individual patients’ anticoagulation therapy data to predict their future levels of anticoagulation. The r...
Simon McDonald, Costas S. Xydeas, Plamen P. Angelo...
Classification algorithms typically induce population-wide models that are trained to perform well on average on expected future instances. We introduce a Bayesian framework for l...
The next development in building Bayesian networks will most likely entail constructing multipurpose models that can be employed for varying tasks and by different types of user. ...
Hermina J. M. Tabachneck-Schijf, Linda C. van der ...
A new training algorithm is presented for delayed reinforcement learning problems that does not assume the existence of a critic model and employs the polytope optimization algorit...
This paper presents the development of two related machine-learned models which predict (a) whether a student can answer correctly questions in an ILE without requesting help and (...