Order of experimentation and advisability of corner measurements

Abstract Basically two questions are examined regarding the design of experiments. First, for what settings is the placement of design points in the corners of the input space advisable in order to achieve a good generalization performance. And second, what order of experimentation leads to the best model quality in early stages of the measurement process. The effect of the explicit addition of corner measurements to three space-filling experimental designs is investigated. It turns out that for most cases the incorporation of corner points harms the model quality. Two new methods to determine the order of experimentation are compared to one active learning strategy and a simple randomization of the measurement sequence. Both order determination methods prove to outperform the random sequences significantly and are only slightly inferior to the active learning strategy.

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