An evolutionary-based approach to learning multiple decision models from underrepresented data
Abstract
The use of multiple Decision Models (DMs) enables to enhance the accuracy in decisions and at the same time allows users to evaluate the confidence in decision making. In this paper we explore the ability of multiple DMs to learn from a small amount of verified data. This becomes important when data samples are difficult to collect and verify. We propose an evolutionary-based approach to solving this problem. The proposed technique is examined on a few clinical problems presented by a small amount of data.Citation
Schetinin, V., Li, D., Maple, C. (2008) An Evolutionary-Based Approach to Learning Multiple Decision Models from Underrepresented Data, The 4th International Conference on Natural Computation (ICNC'08), 1, pp.40-44Type
Conference papers, meetings and proceedingsLanguage
enISBN
9780769533049ae974a485f413a2113503eed53cd6c53
10.1109/ICNC.2008.409