首页|Reports on Machine Learning from University of Liege Provide New Insights (Asses sing Traditional and Machine Learning Methods To Smooth and Impute Device-based Body Condition Score Throughout the Lactation In Dairy Cows)
Reports on Machine Learning from University of Liege Provide New Insights (Asses sing Traditional and Machine Learning Methods To Smooth and Impute Device-based Body Condition Score Throughout the Lactation In Dairy Cows)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on Ma chine Learning. According to news reporting outof Gembloux, Belgium, by NewsRx editors, research stated, “Regular monitoring of body condition score(BCS) chan ges during lactation is an essential management tool in dairy cattle; however, t he currentBCS measurements are often discontinuous and unevenly spaced in time. The imputation of BCS valuesis useful for two main reasons: i) achieving compl eteness of data is necessary to be able to relate BCS toother traits (e.g. milk yield and milk composition) that have been routinely recorded at different time sand with a different frequency, and ii) having expected BCS values provides th e possibility to trigger earlywarnings for animals with certain unexpected cond itions.”
GemblouxBelgiumEuropeCyborgsEmer ging TechnologiesMachine LearningUniversity of Liege
NETL
NSTL
