Free online MAE Calculator – Calculate the Mean Absolute Error (MAE) with our easy-to-use calculator. Enter your predicted and actual values, then click the calculate button.
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| Mean Absolute Error (MAE): |
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.