Type

Other / n/a

Authors

Michael Doherty
Stephen Butler
Laurence Shalloo
John Dunnion
Luke O'Grady
Caroline Fenlon

Subjects

Agriculture & Food Science

Topics
multivariate model reproductive performance logistic regression model ireland insemination coutcome dairy cows data mining decision tree learning

A comparison of machine learning techniques for predicting insemination outcome in Irish dairy cows (2016)

Abstract Reproductive performance has an important effect on economic efficiency in dairy farms with short yearly periods of breeding.The individual factors affecting the outcome of an artificial inseminationhave been extensively researched in many univariate models. In thisstudy, these factors are analysed in combination to create a comprehensivemultivariate model of conception in Irish dairy cows. Logisticregression, Naive Bayes, Decision Tree learning and Random Forests aretrained using 2,723 artificial insemination records from Irish researchfarms. An additional 4,205 breeding events from commercial dairy farmsare used to evaluate and compare the performance of each data miningtechnique. The models are assessed in terms of both discrimination andcalibration ability. The logistic regression model was found to be themost useful model for predicting insemination outcome. This model isproposed as being appropriate for use in decision support and in generalsimulation of Irish dairy cows.
Collections Ireland -> Teagasc -> Animal & Bioscience

Full list of authors on original publication

Michael Doherty, Stephen Butler, Laurence Shalloo, John Dunnion, Luke O'Grady, Caroline Fenlon

Experts in our system

1
Michael L. Doherty
Teagasc
Total Publications: 119
 
2
S T Butler
Teagasc
Total Publications: 89
 
3
Laurence Shalloo
Teagasc
Total Publications: 77
 
 
5
Luke O'Grady
University College Dublin
Total Publications: 54
 
6
Caroline Fenlon
Teagasc
Total Publications: 7