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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Bibliographic Details
Published in:	Machine learning Vol. 107; no. 7; pp. 1119 - 1140
Main Authors:	Muggleton, Stephen H., Schmid, Ute, Zeller, Christina, Tamaddoni-Nezhad, Alireza, Besold, Tarek
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.07.2018 Springer Nature B.V
Subjects:	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
Online Access:	Get full text
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