Milk yield prediction in Friesian cows using linear and flexible discriminant analysis under assumptions violations

The application of novel technologies is now widely used to assist in making optimal decisions. This study aimed to evaluate the performance of linear discriminant analysis (LDA) and flexible discriminant analysis (FDA) in classifying and predicting Friesian cattle's milk production into low ([Formula: see text]4500 kg), medium (4500-7500 kg), and high ([Formula: see text]7500 kg) categories. A total of 3793 lactation records from cows calved between 2009 and 2020 were collected to examine some predictors such as age at first calving (AFC), lactation order (LO), days open (DO), days in milk (DIM), dry period (DP), calving season (CFS), 305-day milk yield (305-MY), calving interval (CI), and total breeding per conception (TBRD). The comparison between LDA and FDA models was based on the significance of coefficients, total accuracy, sensitivity, precision, and F1-score. The LDA results revealed that DIM and 305-MY were the significant (P