Classification of Dairy Cattle Combined Milk Production and Methane Emission Levels via Multilabel & Multiclass Systems

Finding Dairy Cattle (DC) which can produce high levels of milk while emitting low levels of methane (CH4) is a key goal for agriculture. We applied two classification systems in the prediction of DC production and emission levels combined. A Multilabel system (MLS), which utilised an individual model for the prediction of each individual phenotype of the combination, and a Multiclass system (MCS), which applied a single model in the direct prediction of the phenotypes pre-combined. The mean difference between the MLS and MCS systems was not statistically significant (p > 0.05), scoring an overall average accuracy of 66% and 65% respectively. For combined classes which contain relationships between the components that make them up, it is perhaps a MCS which is more appropriate, as it can take in to account these relationships during training, achieving higher precision at the expense of lower recall, while the individual models of the MLS are perhaps best suited to the prediction of each phenotype in isolation, as the blind combination of their predictions may lead to excess false positives. However, the combination of both systems themselves may potentially address the shortcomings of the other, which we intend to investigate in future studies.