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| Mean Absolute Error (MAE): |
Free online MAE Calculator – Calculate the Mean Absolute Error (MAE). Enter your predicted and actual values, then click the calculate button.
Mean Absolute Error (MAE) Formula
The formula for mean absolute error (MAE) is as follows:
MAE = (1/n) * Σ|Ai – Pi|
where:
- MAE = mean absolute error
Σ = summation operator
Pi = predicted value for the ith observation
Ai = observed value(Actual Value) for the ith observation
n = number of observations
How to calculate mean absolute error?
To calculate the Mean Absolute Error (MAE) for a predictive model, follow these steps:
Step 1: Collect Data: Gather the dataset with the true (actual) values of the target variable and the predicted values obtained from your model.
Step 2: Calculate Absolute Errors:
Absolute Error = |Observed value – Predicted value|
Step 3: Sum the Absolute Errors: Add up all the absolute errors obtained in the previous step to get the total sum of absolute errors.
Step 4: Calculate the Mean: Divide the total sum of absolute errors by the number of data points (n) to get the Mean Absolute Error.