MAE in statistics and Machine Learning (ML) stands for the Mean Absolute Error. MAE is the average of the sum of the differences between the actual and predicted values in a dataset. In other words the MAE is the calculation of the the average of the residuals. MAE is expressed by the following mathematical formula. ... Read more
MSE in Machine Learning (ML) stands for Mean Squared Error and is an error calculation formula. MSE calculates the average value of the square power of the sum of differences between the original and predicted values in a dataset. It is similar to MAE, in that MSE is a calculation for the variance of residuals, ... Read more
RMSE is simply the root of the MSE statistical metric. RMSE stands for Root Mean Squared Error. The RMSE is in the same metric scale as the observed parameters, same as the MAE metric. RMSE is a calculation for the standard deviation of residuals. Compared to RMSE, MSE is a calculation of the variance of ... Read more
