Definition
Evolutionary kernel learning stands for using evolutionary algorithms to design the kernel function for a kernel method.
Motivation and Background
In kernel-based learning algorithms, the kernel function implicitly defines the feature space in which the algorithm operates. The kernel determines the scalar product and thereby the metric in the feature space. Choosing the right kernel function is crucial for the training accuracy and generalization performance of the learning machine. The choice may also influence the runtime and storage complexity during and after training.
The kernel is usually not adapted by the kernel method itself; choosing it is a model selectionproblem. In practice, the kernel function is selected from an a priori fixed class. When a parameterized family of kernel functions is considered, kernel adaptation reduces to finding appropriate parameters. The most frequently used method to determine these values is grid search. In simple grid search, the...
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Igel, C. (2016). Evolutionary Kernel Learning. 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_93-1
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DOI: https://doi.org/10.1007/978-1-4899-7502-7_93-1
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