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

  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},
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
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