XCSF for prediction on emotion induced by image based on dimensional theory of emotion
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
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In this article, two learning classifier systems based on evolutionary techniques are described to classify remote sensing images. Usually, these images contain voluminous, complex, and sometimes erroneous and noisy data. The first approach implements ICU, an evolutionary rule discovery system, generating simple and robust rules. The second approach applies the real-valued accuracy-based classifi- cation system XCSR. The two algorithms are detailed and validated on hyperspectral data.