2023
DOI: 10.48550/arxiv.2301.09524
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RF+clust for Leave-One-Problem-Out Performance Prediction

Abstract: Per-instance automated algorithm configuration and selection are gaining significant moments in evolutionary computation in recent years. Two crucial, sometimes implicit, ingredients for these automated machine learning (AutoML) methods are 1) feature-based representations of the problem instances and 2) performance prediction methods that take the features as input to estimate how well a specific algorithm instance will perform on a given problem instance. Nonsurprisingly, common machine learning models fail … Show more

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