Predicting mastitis in dairy cows using neural networks and generalized additive models: A comparison
Study on detecting mastitis of cows from panel of indicators from online data. The neural networks and generalized additive models were used for classification. The classification results are presented in terms of sensitivity and specificity. Methods were similar in their ability to detect mastitis, for fixed specificity of 80%, sensitivity was around 75%. Absence of SCS in the models decreases the ability of prediction by almost 5%.
mastitis online data modeling techniques