title: A novel behavioral model of the pasture-based dairy cow from GPS data using data mining and machine learning techniques.
abstract: A better understanding of the behavior of individual grazing dairy cattle will assist in improving productivity and welfare. Global positioning systems (GPS) applied to cows could provide a means of monitoring grazing herds while overcoming the substantial efforts required for manual observation. Any model of behavioral prediction using GPS needs to be accurate and robust by accounting for inter-cow variation as well as atmospheric effects. We evaluated the performance using a series of machine learning algorithms on GPS data collected from 40 pasture-based dairy cows over 4 mo. A feature extraction step was performed on the collected raw GPS data, which resulted in 43 different attributes. The evaluated behaviors were grazing, resting, and walking. Classifier learners were built using 10 times 10-fold cross validation and tested on an independent test set. Results were evaluated using a variety of statistical significance tests across all parameters. We found that final model selection depended upon level of performance and model complexity. The classifier learner deemed most suitable for this particular problem was JRip, a rule-based learner (classification accuracy=0.85; false positive rate=0.10; F-measure=0.76; area under the receiver operating curve=0.87). This model will be used in further studies to assess the behavior and welfare of pasture-based dairy cows.
authors.affiliation: Institute of Biological, Environmental and Rural Science, Aberystwyth University, Penglais Campus, Ceredigion, SY23 3DA, United Kingdom.
authors.forename: M L
authors.initials: ML
authors.lastname: Williams
authors.affiliation: Department of Computer Science, Institute of Maths, Physics and Computer Science (IMPACS), Aberystwyth University, Penglais Campus, Ceredigion, SY23 3DB, United Kingdom.
authors.forename: N
authors.initials: N
authors.lastname: Mac Parthaláin
authors.affiliation: Department of Geography and Earth Sciences, Aberystwyth University, Penglais Campus, Ceredigion, SY23 3DB, United Kingdom.
authors.forename: P
authors.initials: P
authors.lastname: Brewer
authors.affiliation: Institute of Biological, Environmental and Rural Science, Aberystwyth University, Penglais Campus, Ceredigion, SY23 3DA, United Kingdom.
authors.forename: W P J
authors.initials: WPJ
authors.lastname: James
authors.affiliation: Institute of Biological, Environmental and Rural Science, Aberystwyth University, Penglais Campus, Ceredigion, SY23 3DA, United Kingdom. Electronic address: mir@aber.ac.uk.
authors.forename: M T
authors.initials: MT
authors.lastname: Rose
mesh_terms: D000465:Algorithms; D000818:Animals; D002417:Cattle; D057225:Data Mining; D005260:Female; D040362:Geographic Information Systems; D060434:Herbivory / Q000502:physiology*; D000069550:Machine Learning; D015203:Reproducibility of Results; D012146:Rest / Q000502:physiology*; D016138:Walking / Q000502:physiology*
keywords: GPS; behavior model; data mining; grazing