Reducing one class of machine learning algorithms to logical operations of plausible reasoning

DOI10.1134/S1064230709030083zbMath1308.68100MaRDI QIDQ2017512

K. A. Naidenova

Publication date: 23 March 2015

Published in: Journal of Computer and Systems Sciences International (Search for Journal in Brave)

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Reasoning under uncertainty in the context of artificial intelligence (68T37)

Uses Software

• TANE

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Partition semantics for relations
• Attributive concept descriptions with complements
• Concept lattices and conceptual knowledge systems
• On the complexity of inferring functional dependencies
• A fast algorithm for building lattices
• On the irredundant generation of knowledge spaces
• A study of relevance for learning in deductive databases
• Tane: An Efficient Algorithm for Discovering Functional and Approximate Dependencies
• Algorithms for inferring functional dependencies from relations
• Inductive Logic Programming: Theory and methods
• Comparing performance of algorithms for generating concept lattices
• Relations binaires, fermetures, correspondances de Galois
• Galois Connexions
• Inducing multi-level association rules from multiple relations

This page was built for publication: Reducing one class of machine learning algorithms to logical operations of plausible reasoning