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Questions tagged [mae]

The Mean Absolute Error (MAE) is a point forecast accuracy measure. In the forecasting literature, Mean Absolute Deviation (MAD) is used interchangeably.

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Comparison of MAE and Mean to illustrate the error magnitude

I have predicted a time series with positive, zero and negative values. As error measurement I used the Mean Absolute Error (MAE). In order to give the reader of my paper a better understanding ...
13 views

If predicted responses has an RMSE/MAE, how often will a prediction fall below the error? [closed]

As the title asks, If I for instance has a regression based model with an error rate, either in terms of RMSE (could be interpreted as a standard deviation?) or MAE, how often will the predicted value ...
18 views

Learning Curves using different models

I am running repeated K-fold Cross-Validation on my dataset using different models. My problem is a regression problem and I am counting on the error metric MAE. I do know that some models may behave ...
25 views

Dividing the MAE by the average of the values

I would like to parse the MAE (Mean Absolute Error) to a percentage value. I know there is the MAPE (Mean Absolute Percentage Error), however it has some drawbacks as going to infinity if one of my ...
986 views

Can RMSE and MAE have the same value?

I am implementing cross validation and calculating error metrics such as RMSE, $R^2$, MAE, MSE, etc. Can RMSE and MAE have the same value?
48 views

RSME, MAE and prediction interval [closed]

Could someone please clarify, whether it is appropriate to define a prediction interval or an equivalent for an RMSE and MAE measure. If so, could you please suggest how such an interval is defined.
50 views

MSE Intuition and Interpretation

I've got a very small question. Say I'm making a linear regression model. When I test the model with a testing set, I get an MSE of 4.31 (arbitrary). What do I interpret from this? As in, what does ...
60 views

Error distribution for Huber Regression

For linear regression there's an assumption that error terms come from normal distribution. so that $Y = aX + b + \epsilon$, where $\epsilon$ has normal distribution with mean zero and certain ...
38 views

How does MAE as objective function impact gradient boosting training compared to MSE?

I have a regression problem where I want to minimize MAE as a business metric. I'm using LightGBM. I initially used the default objective function for regression ...
80 views

a measure for MAE (of a regression)

I'm running a grid search, in order to fine-tune a NN hyper parameters. the question is: the MAE values I get from the trainings are too close. since I have the statistical attributes of the target ...
168 views

Standardised mean absolute error (SMAE) and how to calculate it?

I am using the mean absolute error mean(abs(obs - pred)) as one of the measures assessing the fit of my model. I would also like to have a standardised measure ...
97 views

What is the best point forecast for gamma distributed data?

I believe that the values I am forecasting are gamma distributed with shape $k>0$ and scale $\theta>0$. I need a point forecast (i.e., a one-number summary) that minimizes the expected error. ...
104 views

What is the best point forecast for lognormally distributed data?

I believe that the values I am forecasting are lognormally distributed with log-mean $\mu$ and log-variance $\sigma^2$. I need a point forecast (i.e., a one-number summary) that minimizes the expected ...
316 views

calculating overall error in k-fold cross validation

when using k-fold cross validation i thought the overall error was equal to the mean of errors of each fold. the error being anything from MAE and RMSE to NDCG,F-measure, precision and recall. however ...
438 views

Mean Absolute Error in Random Forest Regression

I am new to the whole ML scene and am trying to resolve the Allstate Kaggle challenge to get a better feeling for the Random Forest Regression technique. The challenge is evaluated based on the MAE ...
32 views

How to best evaluate a cross validation of a logistic regression using cbind

I ran a logistic GLMM using cbind for the response: ...
27 views

2k views

Why not using the R squared to measure forecast accuracy?

Why in literature usually the common accuracy measures like MAD, MSE, RMSE, MAPE ... are used. Why not using the $R^2$ (coefficient of determination)? I was thinking about the difference: By using ...
99 views

Forecasting Prediction Accuracy

Out of 4 error paramters which one is best for evaluating prediction accuracy? Average error Mean absolute error Mean squared error Mean absolute % error why?
410 views

Mean Absolute Error and Data Distribution

I use a memory-based learning model to predict human scores in a [0, 10] range (quiz results). As a forecast error metric I use Mean Absolute Error. I was wondering what is the relation between MAE ...
930 views

Measuring forecast accuracy

We're forecasting sales data for one of our clients on a weekly basis. Sales is forecasted for each organizational unit. The sales data is forecasted via different algorithms and/or algorithm ...
11k views

Which is the best accuracy measuring criteria among rmse, mae & mape?

I have created training set and test set from my data. Then I performed auto.arima() and ets() in R on the training set to predict one-step ahead forecasts. These were then compared with the test set ...