多变量检验中田口方法与进化优化方法的比较
A Comparison of the Taguchi Method and Evolutionary Optimization in Multivariate Testing
摘要：
多元测试最近成为Web界面设计中一种很有前途的技术。与标准的A/B测试不同，多变量方法旨在系统地评估少数关键变量的大量值。田口方法是这一思想的实际实现，专注于值的正交组合。本文评估了一种替代方法：基于种群的搜索，即进化优化。它的性能进行比较，田口方法在几个模拟条件下，包括正交设计有利于田口方法，和两个现实的条件与变量之间的依赖关系。进化优化被发现表现得更好，特别是在现实的条件下，这表明它形成了一个很好的方法，在未来的Web界面设计。
英文摘要：
Multivariate testing has recently emerged as a promising technique in web interface design. In contrast to the standard A/B testing, multivariate approach aims at evaluating a large number of values in a few key variables systematically. The Taguchi method is a practical implementation of this idea, focusing on orthogonal combinations of values. This paper evaluates an alternative method: population-based search, i.e. evolutionary optimization. Its performance is compared to that of the Taguchi method in several simulated conditions, including an orthogonal one designed to favor the Taguchi method, and two realistic conditions with dependences between variables. Evolutionary optimization is found to perform significantly better especially in the realistic conditions, suggesting that it forms a good approach for web interface design in the future.
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