Combining model-based and instance-based learning for first order regression

@inproceedings{Driessens2005CombiningMA,
  title={Combining model-based and instance-based learning for first order regression},
  author={Kurt Driessens and Saso Dzeroski},
  booktitle={ICML},
  year={2005}
}
The introduction of relational reinforcement learning and the RRL algorithm gave rise to the development of several first order regression algorithms. So far, these algorithms have employed either a model-based approach or an instance-based approach. As a consequence, they suffer from the typical drawbacks of model-based learning such as coarse function approximation or those of lazy learning such as high computational intensity.In this paper we develop a new regression algorithm that combines… CONTINUE READING
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