Phan, Thong H.Witten, Ian H.2008-10-232008-10-231994-08Phan, T.H. & Witten, I.H. (1994). Data transformation: a semantically-based approach to function discovery. (Working paper 94/15). Hamilton, New Zealand: University of Waikato, Department of Computer Science.1170-487Xhttps://hdl.handle.net/10289/1144This paper presents the method of data transformation for discovering numeric functions from their examples. Based on the idea of transformations between functions, this method can be viewed as a semantic counterpart to the more common approach of formula construction used in most previous discovery systems. Advantages of the new method include a flexible implementation through the design of transformation rules, and a sound basis for rigorous mathematical analysis to characterize what can be discovered. The method has been implemented in a discovery system called "LINUS," which can identify a wide range of functions: rational functions, quadratic relations, and many transcendental functions, as well as those that can be transformed to rational functions by combinations of differentiation, logarithm and function inverse operations.application/pdfenFunction discoverydata transformationMachine learningWorking Paper