Non-informative features and a scale-only feature achieve strong prediction errors under common algorithm-selection evaluation schemes, without actually selecting better algorithms.
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The Pitfalls of Benchmarking in Algorithm Selection: What We Are Getting Wrong
Non-informative features and a scale-only feature achieve strong prediction errors under common algorithm-selection evaluation schemes, without actually selecting better algorithms.