Titlebook: Handbook of Evolutionary Machine Learning; Wolfgang Banzhaf,Penousal Machado,Mengjie Zhang Book 2024 The Editor(s) (if applicable) and The

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Evolutionary Regression and Modellingintroduce the ideas behind various evolutionary computation methods for regression and present a review of the efforts on enhancing learning capability, generalisation, interpretability and imputation of missing data in evolutionary computation for regression.

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Evolutionary Classificationthis research area is .. This chapter introduces the fundamental concepts of evolutionary classification, followed by the key ideas using evolutionary computation techniques to address existing classification challenges such as multi-class classification, unbalanced data, explainable/interpretable classifiers and transfer learning.

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Evolutionary Computation and the Reinforcement Learning Problemecies that rapidly adapt to environmental change and acquire new problem-solving skills through experience. Reinforcement Learning (RL) is a machine learning problem in which an agent must learn how to map situations to actions in an unknown world in order to maximise the sum of future rewards. Ther

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Evolutionary Regression and Modellingry from data. Symbolic regression goes a step further by learning explicitly symbolic models from data that are potentially interpretable. This chapter provides an overview of evolutionary computation techniques for regression and modelling including coefficient learning and symbolic regression. We

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