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      •   Research Commons
      • University of Waikato Research
      • Computing and Mathematical Sciences
      • Computer Science Working Paper Series
      • 1995 Working Papers
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      •   Research Commons
      • University of Waikato Research
      • Computing and Mathematical Sciences
      • Computer Science Working Paper Series
      • 1995 Working Papers
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      An investigation into the use of machine learning for determining oestrus in cows

      Mitchell, R. Scott; Sherlock, Robert A.; Smith, Lloyd A.
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      Mitchell, R. S., Sherlock, R. A. & Smith, L. A. (1995) An investigation into the use of machine learning for determining oestrus in cows. (Working paper 95/23). Hamilton, New Zealand: University of Waikato, Department of Computer Science.
      Permanent Research Commons link: https://hdl.handle.net/10289/1100
      Abstract
      A preliminary investigation of the application of two well-known machine learning schemes—C4.5 and FOIL—to detection of oestrus in dairy cows has been made. This is a problem of practical economic significance as each missed opportunity for artificial insemination results in 21 days lost milk production. Classifications were made on normalised deviations of milk volume production and milking order time series data. The best learning scheme was C4.5 which was able to detect 69% of oestrus events, albeit with an unacceptably high rate of "false positives" (74%). Several directions for further work and improvements are identified.
      Date
      1995-08
      Type
      Working Paper
      Series
      Computer Science Working Papers
      Report No.
      95/23
      Publisher
      University of Waikato, Department of Computer Science
      Collections
      • 1995 Working Papers [32]
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