Decision trees, entropy, and the contrastive feature hierarchy

Dresher (2009) argues that language-particular hierarchies of features are the best way to identify contrastive in a phonological inventory. While not universal, this ordering is also fully unconstrained. But what limits space possible feature orders remains an open question. This paper demonstrates how concept entropy establishes partial both allows for but constrains variation. Specifically, decision tree machine learning algorithm employed dynamically impose structure on hypothesis orders.