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

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, tende...

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Vydané v:	Machine learning Ročník 107; číslo 7; s. 1119 - 1140
Hlavní autori:	Muggleton, Stephen H., Schmid, Ute, Zeller, Christina, Tamaddoni-Nezhad, Alireza, Besold, Tarek
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer US 01.07.2018 Springer Nature B.V
Predmet:	Accuracy Artificial Intelligence Computer Science Control Hypotheses Logic programs Machine learning Mechatronics Natural Language Processing (NLP) Performance prediction Robotics Simulation and Modeling Special Issue of the Inductive Logic Programming (ILP) 2016 Inductive logic programming Comprehensibility Ultra-strong machine learning
ISSN:	0885-6125, 1573-0565
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