Calculating the Mean Absolute Error

The mean absolute error (mae) is a metric for determining the similarity between two sets.
The error between two numbers is simply the difference between them.
The absolute error is the absolute difference.
To find the mean absolute error:
- Find the absolute error between corresponding values in the sets
- Then find the mean of those errors.

Find the mean absolute error of the following two sets of numbers:
```
S₁ = [2, 5, 9, 2]
S₂ = [6, 3, 6, 1]
```

First we calculate the differences between these numbers:
```
D = [2 - 6, 5 - 3, 9 - 6, 2 - 1]
D = [-4, 2, 3, 1]
```
Now we must make these numbers absolute:
```
D = [4, 2, 3, 1]
```

Finally, we find the mean of these numbers:

mae = (4 + 2 + 3 + 1) / 4
mae = 10 / 4
mae = 2.5

LaTeX formula:mae = (\frac{1}{n})\sum_{i=1}^{n}\left | y_{i} - x_{i} \right |

import sklearn.metrics

S1 = [2, 5, 9, 2]
S2 = [6, 3, 6, 1]

mae = sklearn.metrics.mean_absolute_error(S1, S2)
print(mae)

Prerequisites