Witten, I. H., Holmes, G., McQueen, R. J., Smith, L. A., & Cunningham, S. J. (1993). Practical machine learning and its application to problems in agriculture (Computer Science Working Papers 93/1). Hamilton, New Zealand: Department of Computer Science, University of Waikato.
Permanent Research Commons link: https://hdl.handle.net/10289/9915
One of the most exciting and potentially far-reaching developments in contemporary computer science is the invention and application of methods of machine learning. These have evolved from simple adaptive parameter-estimation techniques to ways of (a) inducing classification rules from examples, (b) using prior knowledge to guide the interpretation of new examples, (c) using this interpretation to sharpen and refine the domain knowledge, and (d) storing and indexing example cases in ways that highlight their similarities and differences. Such techniques have been applied in domains ranging from the diagnosis of plant disease to the interpretation of medical test date. This paper reviews selected methods of machine learning with an emphasis on practical applications, and suggests how they might be used to address some important problems in the agriculture industries.
Department of Computer Science, University of Waikato
© 1993 by Ian H. Witten. Geoffrey Holmes. RobertJ. McQueen, Lloyd Smith, Sally Jo Cunningham
- 1993 Working Papers