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Research Hasselt University


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project R-8173

Title : Rough Cognitive Networks for multi-label classification. (R-8173)
Abstract: Rough Cognitive Networks (RCNs) a recently introduced classification model that allow elucidating their decision process. This transparent classifier augments the neural reasoning scheme of Fuzzy Cognitive Maps with information granules coming from Rough Set Theory. RCN-based classifiers have proven effective in solving a wide variety of standard classification problems. The accuracy and transparency of RCN-based models encouraged us to investigate their performance in Multi-label classification (MLC) scenarios, which have arisen as an extension of standard classification problems in which each input object is associated with multiple labels. The RCN model involves three key steps, namely (1) the granulation of the example space, (2) the network design and (3) the network exploitation. In order to adapt the RCN mode to the MLC context, these septs must be modified. The envisaged research will result in a RCN-based algorithm able to solve different types of MLC problems, being both theoretically sound and transparent, yielding high prediction rates and computationally more efficiently that the existing MLC procedures.
Period of project : 7/07/2017to31/12/2020