A machine learning approach using partitioning around medoids clustering and random forest classification to model groups of farms in regard to production parameters and bulk tank milk antibody status of two major internal parasites in dairy cows

HIGHLIGHTS

• who: Andreas W. Oehm and colleagues from the Oberschleissheim, Germany, Institute for Parasitology, Centre for Infection Medicine, University of have published the research: A machine learning approach using partitioning around medoids clustering and random forest classification to model groups of farms in regard to production parameters and bulk tank milk antibody status of two major internal parasites in dairy cows, in the Journal: PLOS ONE of 13/02/2022
• what: The aims of this study were to explore if different clusters can be identified for farm-level bulk tank milk F. hepatica as well as . . .
  

   

  

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