Research Commons
      • Browse 
        • Communities & Collections
        • Titles
        • Authors
        • By Issue Date
        • Subjects
        • Types
        • Series
      • Help 
        • About
        • Collection Policy
        • OA Mandate Guidelines
        • Guidelines FAQ
        • Contact Us
      • My Account 
        • Sign In
        • Register
      View Item 
      •   Research Commons
      • University of Waikato Research
      • Computing and Mathematical Sciences
      • Computer Science Working Paper Series
      • 1993 Working Papers
      • View Item
      •   Research Commons
      • University of Waikato Research
      • Computing and Mathematical Sciences
      • Computer Science Working Paper Series
      • 1993 Working Papers
      • View Item
      JavaScript is disabled for your browser. Some features of this site may not work without it.

      Practical machine learning and its application to problems in agriculture

      Witten, Ian H.; Holmes, Geoffrey; McQueen, Robert J.; Smith, Lloyd A.; Cunningham, Sally Jo
      Thumbnail
      Files
      uow-cs-wp-1993-01.pdf
      Published version, 3.673Mb
      Find in your library  
      Citation
      Export citation
      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
      Abstract
      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.
      Date
      1993
      Type
      Working Paper
      Series
      Computer Science Working Papers
      Report No.
      93/1
      Publisher
      Department of Computer Science, University of Waikato
      Rights
      © 1993 by Ian H. Witten. Geoffrey Holmes. RobertJ. McQueen, Lloyd Smith, Sally Jo Cunningham
      Collections
      • 1993 Working Papers [12]
      Show full item record  

      Usage

      Downloads, last 12 months
      142
       
       

      Usage Statistics

      For this itemFor all of Research Commons

      The University of Waikato - Te Whare Wānanga o WaikatoFeedback and RequestsCopyright and Legal Statement