Broiler chickens can benefit from machine learning: Support vector machine analysis of observational epidemiological data

Journal of the Royal Society Interface

Volumn 9, Issue 73, 2012, Pages 1934-1942

  Hepworth, Philip J ^a   Nefedov, Alexey V ^a,b   Muchnik, Ilya B ^b   Morgan, Kenton L ^a  

^a UNIVERSITY OF LIVERPOOL   (United Kingdom)

^b RUTGERS UNIVERSITY   (United States)

Author keywords

Broiler; Classification; Hock burn; Machine learning; Risk factor; Support vector machine

Indexed keywords

CLASSIFICATION (OF INFORMATION); LEARNING SYSTEMS; LOGISTICS; SUPPORT VECTOR MACHINES;

BROILER; BROILER CHICKENS; DAILY LIVES; FARM MANAGEMENT; HOCK BURN; LOGISTIC REGRESSIONS; MACHINE LEARNING TECHNIQUES; MANAGEMENT SYSTEMS; NOVEL APPLICATIONS; RECEIVER OPERATING CHARACTERISTIC CURVES; RISK FACTORS; SUPERVISED MACHINE LEARNING; SUPPORT VECTOR;

LEARNING ALGORITHMS;

ANIMAL HEALTH; ANIMAL WELFARE; ARTICLE; BROILER; BURN; CHICKEN; CONTROLLED STUDY; DERMATITIS; FARMING SYSTEM; MACHINE LEARNING; NONHUMAN; POULTRY;

EID: 84865076648     PISSN: 17425689     EISSN: 17425662     Source Type: Journal    
DOI: 10.1098/rsif.2011.0852     Document Type: Article

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