I have used a few regression models on the same dataset and obtained error metrics for them as shown below,
The RMSE(Root Mean Squared Error) and MAE(Mean Absolute Error) for model A is lower than that of model B where the R2 score is higher in model A. According to my knowledge this means that model A provides better predictions than model B. But when considering the MAPE (Mean Absolute Percentage Error) model B seems to have a lower value than model A. I would really appreciate it if someone could explain why it is so. Thanks in advance.