This study compares multinomial and ordinal logistic regression models using custom penalized error metrics. By applying larger penalties for misordered predictions, the performance of each model is assessed through penalized Mean Absolute Error (MAE) and Mean Squared Error (MSE), highlighting the benefits of considering order in predictive accuracy.

Tarea 2 de la materia Modelación de Sistemas por Javier Cázares Salinas