What is Homogenous Groups

Tanzania's small-scale dairy industry faces similar challenges to those of other developing nations whereby insufficient infrastructure, outdated technology, and low productivity are serious problems for higher milk yield. Tanzania urgently needs to adopt cutting-edge solutions in order to boost dairy performance. With 3500 households' secondary data and 202 households' primary data from 8 villages throughout the Kilimanjaro and Arusha regions, this chapter demonstrates the use of machine learning (ML) techniques to derive homogeneous production clusters and recommendations for more milk yield among dairy farmers. The likelihood for higher milk yield is demonstrated for various clusters with the use of support, confidence, and lift values of association rules analysis. Finally, the production clusters and recommendations are deployed through a mobile application. Recommendations for future improvement are suggested especially on further deployment of learning recommendations and development of a platform-independent mobile solution.