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.