Abstract
The notion of homogeneous logical proportions has been recently introduced in close relation with the idea of analogical proportion. The four homogeneous proportions have intuitive meanings, which can be related with classification tasks. In this paper, we proposed a supervised classification algorithm using homogeneous logical proportions and provide results for all. A final comparison with previous works using similar methodologies and with other classifiers is provided.
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Moraes, R.M., Machado, L.S., Prade, H., Richard, G. (2013). Supervised Classification Using Homogeneous Logical Proportions for Binary and Nominal Features. In: Ruiz-Shulcloper, J., Sanniti di Baja, G. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2013. Lecture Notes in Computer Science, vol 8258. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41822-8_21
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DOI: https://doi.org/10.1007/978-3-642-41822-8_21
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