Abstract
From the basis of the combination of supervised classification and bipolar knowledge representation, we explore in this proposal a new approach for the exploitation of the bipolar classification scores. The proposed approach is based on fitting a rule-based classifier to determine the decision rule that produces the final class assignments on the basis of the bipolar scores provided by any soft classifier. Therefore, the proposed method can be seen as a generalization of ROC-curve based decision rules, that takes advantage of the extra information introduced through the bipolar knowledge representation. The presented experimental results shows the feasibility of the proposed approach.
Supported by FORAID Research Group by means of grant PGC2018-096509-B-I00 of the Government of Spain.
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Villarino, G., Gómez, D., Rodríguez, J.T., Fernández, A. (2022). A New Exploitation Scheme in the Context of Bipolar Classifiers. In: Cornejo, M.E., Kóczy, L.T., Medina-Moreno, J., Moreno-García, J. (eds) Computational Intelligence and Mathematics for Tackling Complex Problems 2. Studies in Computational Intelligence, vol 955. Springer, Cham. https://doi.org/10.1007/978-3-030-88817-6_1
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