. Bayoudh, Learning by analogy: A classification rule for binary and nominal data Learning a classifier with very few examples: Analogy based and knowledge based generation of new examples for character recognition, Proc. 18th Europ. Conf. on Machine Learning (ECML'07), pp.678-683, 2007.

. Blum, Self-testing/correcting with applications to numerical problems, Proc. 21st Europ. Conf. on Artificial Intelligence (ECAI'14), pp.549-595, 1993.
DOI : 10.1016/0022-0000(93)90044-W
URL : http://external.nj.nec.com/homepages/ronitt/papers/blr.ps

. Bounhas, Not being at odds with a class: A new way of exploiting neighbors for classification Generalizations of Swierczkowski's lemma and the arity gap of finite functions On a quasi-ordering on Boolean functions Analogical projection in pattern perception, Proc. 22nd Europ. Conf. on Artificial Intelligence (ECAI'16)Couceiro and PouzetDastani et al., 2003] M. Dastani, B. Indurkhya, and R. Scha, pp.1662-16635905, 2003.

R. R. Davies, S. J. Davies, and . Russell, A logical approach to reasoning by analogy, Proc. 10th Int. Joint Conf. on Artificial Intelligence (IJCAI'87), pp.264-270, 1987.

F. Li, P. Li, and P. Perona, One-shot learning of object categories, IEEE Trans. on Pattern Analysis and Machine Intelligence, vol.28, issue.4, pp.594-611, 2006.

. Gentner, The Analogical Mind: Perspectives from Cognitive Science Structure-mapping: A theoretical framework for analogy Metaphors and heuristic-driven theory projection (hdtp) Theoretical Computer Science Analogical classifiers: A theoretical perspective, Proc. 22nd Europ. Conf. on Artificial Intelligence (ECAI'16)] S. Klein. Analogy and mysticism and the structure of culture (and Comments & Reply). Current Anthropology, pp.155-17098, 1983.

]. Y. Lepage, Analogy and Formal Languages, Electronic Notes in Theoretical Computer Science, vol.53, 2001.
DOI : 10.1016/S1571-0661(05)82582-4
URL : https://doi.org/10.1016/s1571-0661(05)82582-4

]. Y. Lepage, De l'analogie rendant compte de la commutation en linguistique. Habilit, Diriger des Recher.Lichman, 2013] M. Lichman. UCI machine learning repository, 2003.
URL : https://hal.archives-ouvertes.fr/tel-00004372

D. Miclet, Miclet and A. Delhay. Relation d'analogie et distance sur un alphabet défini par des traits, 2004.

P. Miclet, H. Miclet, and . Prade, Handling Analogical Proportions in Classical Logic and Fuzzy Logics Settings, Proc. 10th Eur. Conf. on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (EC- SQARU'09), pp.638-650, 2009.
DOI : 10.1007/BFb0017032

. Miclet, Analogical dissimilarity: Definition, algorithms and two experiments in machine learning, J. Artif. Intell. Res. (JAIR), vol.32, pp.793-824, 2008.

R. H. Prade, G. Prade, and . Richard, From Analogical Proportion to Logical Proportions, Logica Universalis, vol.23, issue.12, pp.441-505, 2013.
DOI : 10.1145/359038.359042
URL : https://hal.archives-ouvertes.fr/hal-01138469

A. E. Rumelhart, A. A. Rumelhart, and . Abrahamson, A model for analogical reasoning, Cognitive Psychology, vol.5, issue.1, pp.1-28, 2005.
DOI : 10.1016/0010-0285(73)90023-6

]. A. Salomaa, On essential variables of functions, especially in the algebra of logic, Annales Academiae Scientiarum Fennicae Series A I Mathematica, vol.1964, pp.3-11, 1963.
DOI : 10.5186/aasfm.1964.339

]. M. Stone, The theory of representation for Boolean algebras. Trans, pp.37-111, 1936.

Y. Stroppa, F. Stroppa, and . Yvon, Analogical learning and formal proportions: Definitions and methodological issues, 2005.

]. R. Willard and I. Martin, Essential arities of term operations in finite algebras, Discrete Mathematics, vol.149, issue.1-3, pp.239-259, 1996.
DOI : 10.1016/0012-365X(94)00323-B