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LA home FP HICS2003 & slides II Also see: MML |
Abstract: The specification of various kinds of statistical model from machine learning and data mining is examined formally using the type and class system of the functional programming language Haskell as a meta-language. Types and classes (in the programming sense) of models, and operations on models, are defined; many are naturally polymorphic. Convenient conversion functions map between the classes of models and extend their range of usefulness. The result is a kind of theory of programming with models, not only of using them. The ``theory'' can run as an executable Haskell program or can throw light on the foundations of platforms for programming with statistical models.
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Presented at the Second
Hawaii International Conference on Statistics and Related Fields (HICS03),
Honolulu, |
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Keywords: Model, polymorphism, type, class. [paper (.pdf)], [paper (.ps)] |
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