Abstract
Representation of input data has an essential influence on the performance of machine learning systems. Evolutionary algorithms can be used to transform data representation by selecting some of the existing features (evolutionary feature selection) or constructing new features from the existing ones (evolutionary feature construction). This entry provides the rationale for both these approaches and systematizes the research and applications in this area.
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Krawiec, K. (2016). Evolutionary Feature Selection and Construction. In: Sammut, C., Webb, G. (eds) Encyclopedia of Machine Learning and Data Mining. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7502-7_90-1
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DOI: https://doi.org/10.1007/978-1-4899-7502-7_90-1
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