Article ID Journal Published Year Pages File Type
6858990 International Journal of Approximate Reasoning 2013 18 Pages PDF
Abstract
The effectiveness of the synergy has been tested on twelve datasets. Using non-parametric statistical tests we show that, although achieving statistically equivalent solutions, the adoption of this synergy allows saving up to 97.38% of the execution time with respect to a state-of-the-art multi-objective evolutionary approach which learns rules from scratch.
Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
Authors
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