An investigation into the use of machine learning for determining oestrus in cows
Computers and Electronics in AgriculturePublished 1 August 1996
Rory Mitchell, R. Sherlock, Lloyd A. Smith
Citations41
SJR quartileQ1
SJR score1.83
SNIP2.35
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TL;DR
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, with the best learning scheme being C 4.5, albeit with an unacceptably high rate of “false positives”.
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.
Keywords
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