Application of Bayersian networks for classification of goats on perfomance and grading

Author

Chinhema, Hope T.

Title

Application of Bayersian networks for classification of goats on perfomance and grading

Abstract

Goat performance evaluation encompasses a spectrum of factors, including physical characteristics, health metrics, productivity indicators, and genetic information . These diverse features collectively define the overall performance of goats in areas such as milk production, fiber production, meat quality, and reproductive success. The integration of machine learning facilitates the development of predictive models that discern patterns within these datasets, providing valuable insights for farmers seeking to enhance the quality and productivity of their goat herds.
The researcher developed and implemented a machine learning-based goat classification system with a focus on performance evaluation. The goal was to bridge the gap between traditional, subjective methods and modern, data-driven approaches thereby providing farmers with a more efficient and accurate means of assessing and managing goat herds. Finally the researcher evaluated the accuracy of the model on classifying goats based on performance.

Date

June 2024

Publisher

BUSE

Keywords

Goat performance evaluation,

Integration of machine,

Classifying goats based on performance.

Supervisor

Mr. Zano,