Ultra-Strong Machine Learning: comprehensibility of programs learned with ILP

@article{Muggleton2018UltraStrongML,
  title={Ultra-Strong Machine Learning: comprehensibility of programs learned with ILP},
  author={Stephen Muggleton and Ute Schmid and Christina Zeller and Alireza Tamaddoni-Nezhad and Tarek R. Besold},
  journal={Machine Learning},
  year={2018},
  volume={107},
  pages={1119-1140}
}
During the 1980s Michie defined Machine Learning in terms of two orthogonal axes of performance: predictive accuracy and comprehensibility of generated hypotheses. Since predictive accuracy was readily measurable and comprehensibility not so, later definitions in the 1990s, such as Mitchell’s, tended to use a one-dimensional approach to Machine Learning based solely on predictive accuracy, ultimately favouring statistical over symbolic Machine Learning approaches. In this paper we provide a… CONTINUE READING
Related Discussions
This paper has been referenced on Twitter 19 times. VIEW TWEETS

Similar Papers

Loading similar papers…