Learning in Comparator Networks
We discuss how to train and tune comparators aimed at multi-similarity-based classification of compound objects. The proposed approach is supported by a collection of techniques and algorithms for construction and use of comparator networks. The described methodology has been implemented as a software library and may be used for a variety of future applications.
- 1.Ayodele, T.: Introduction to Machine Learning. INTECH Open Access Publisher (2010)Google Scholar
- 6.Sosnowski, L., Szczuka, M.S.: Recognition of compound objects based on network of comparators. In: Proceedings of FedCSIS 2016, Position Papers, pp. 33–40 (2016)Google Scholar
- 7.Staab, S., Maedche, A.: Knowledge portals: ontologies at work. AI Mag. 22(2), 63–75 (2001)Google Scholar
- 11.Świechowski, M., Kacprzyk, J., Zadrożny, S.: A novel game playing based approach to the modeling and support of consensus reaching in a group of agents. In: Proceedings of SSCI 2016, pp. 1–8 (2016)Google Scholar
- 12.Benitez, M.J., Medina, J., Ślęzak, D.: \(\delta \)-Information reducts and bireducts. In: Proceedings of IFSA-EUSFLAT-15 (2015)Google Scholar