Analogy-based classifiers for nominal or numerical data

DOI10.1016/j.ijar.2017.08.010zbMath1419.68073OpenAlexW2753783655MaRDI QIDQ1679644

Myriam Bounhas, Henri Prade, Gilles Richard

Publication date: 21 November 2017

Published in: International Journal of Approximate Reasoning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ijar.2017.08.010

zbMATH Keywords

classificationnominal datanumerical dataanalogical proportions

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (9)

Analogies between sentences: theoretical aspects -- preliminary experiments ⋮ Multiple analogical proportions ⋮ Analogical Proportions and Binary Trees ⋮ Galois theory for analogical classifiers ⋮ Logical proportions-related classification methods beyond analogy ⋮ Using analogical proportions for explanations ⋮ Analogical proportions, multivalued dependencies and explanations ⋮ Analogical proportions: from equality to inequality ⋮ Classifying and completing word analogies by machine learning

Uses Software

• UCI-ml
• LIBSVM

Cites Work

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• Oddness/evenness-based classifiers for Boolean or numerical data
• Multiple-valued extensions of analogical proportions
• Combining instance-based learning and logistic regression for multilabel classification
• From analogical proportion to logical proportions
• A New View of Conformity and Its Application to Classification
• Handling Analogical Proportions in Classical Logic and Fuzzy Logics Settings
• Analogy and Formal Languages
• Analogical Proportions and Multiple-Valued Logics
• A $k$-Sample Model in Order Statistics
• Analogical Proportions in a Lattice of Sets of Alignments Built on the Common Subwords in a Finite Language

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