Title :
Transferring symbolic knowledge into a RuleNet neural network
Author :
Nicoletti, Mario Do Carmo ; Figueira, Lucas Baggio ; Ramer, Arthur
Author_Institution :
DC-UFSCar, Sao Carlos
Abstract :
This paper investigates the use of symbolic knowledge to initialize a RuleNet neural network learning process. The basic idea is to provide the symbolic knowledge induced by either ID3 or NGE to the RuleNet learning process, as the initial knowledge available. The paper describes experiments conducted using seven knowledge domains and focuses the discussion on the accuracy of the induced concepts. The results show that the collaboration is feasible but not necessarily improves the results obtained by RuleNet on its own
Keywords :
learning (artificial intelligence); neural nets; RuleNet neural network learning process; machine learning; symbolic knowledge; Australia; Bagging; Collaboration; Collaborative work; Gain measurement; Investments; Learning systems; Machine learning; Neural networks; Proposals;
Conference_Titel :
Computational Cybernetics, 2004. ICCC 2004. Second IEEE International Conference on
Conference_Location :
Vienna
Print_ISBN :
0-7803-8588-8
DOI :
10.1109/ICCCYB.2004.1437738
