https://github.com/joegasewicz/regression-error-metrics
Regression Error Metrics
https://github.com/joegasewicz/regression-error-metrics
Last synced: 3 months ago
JSON representation
Regression Error Metrics
- Host: GitHub
- URL: https://github.com/joegasewicz/regression-error-metrics
- Owner: joegasewicz
- Created: 2024-11-18T21:52:50.000Z (11 months ago)
- Default Branch: master
- Last Pushed: 2024-11-20T21:21:36.000Z (11 months ago)
- Last Synced: 2025-04-03T18:09:49.851Z (6 months ago)
- Language: Python
- Size: 8.79 KB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Regression Error Metrics
Library that implements MAE, MSE & RMSE evaluation metrics.
### Mean Absolute Error (MAE)
$$
\text{MAE} = \frac{1}{n} \sum_{i=1}^{n} | y_i - \hat{y}_i |
$$
```python
from mae import MAE
mae = MAE(
actual_vals=[12, 13, 14, 15, 15, 22, 27],
predicted_vals=[11, 13, 14, 14, 15, 16, 18],
)
mae.calc_errors()
mae.set_absolute_vals()
mae.sum_errors()
result = mae.get_mean()
assert round(result, 5) == 2.42857
```
### Mean Squared Error (MSE)
$$
\text{MSE} = \frac{1}{n} \sum_{i=1}^{n} (y_i - \hat{y}_i)^2
$$
```python
from mse import MSE
mse = MSE(
actual_vals=[34, 37, 44, 47, 48, 48, 46, 43, 32, 27, 26, 24],
predicted_vals=[37, 40, 46, 44, 46, 50, 45, 44, 34, 30, 22, 23],
)
mse.calc_errors()
mse.square_errors()
mse.sum_errors()
result = mse.get_mean()
assert round(result, 5) == 5.91667
```
### Root Mean Square Error (RMSE)
$$
\text{RMSE} = \sqrt{\frac{1}{n} \sum_{i=1}^{n} (y_i - \hat{y}_i)^2}
$$
```python
from rmse import RMSE
rmse = RMSE(
actual_vals=[34, 37, 44, 47, 48, 48, 46, 43, 32, 27, 26, 24],
predicted_vals=[37, 40, 46, 44, 46, 50, 45, 44, 34, 30, 22, 23],
)
rmse.calc_errors()
rmse.square_errors()
rmse.sum_errors()
rmse.set_mean()
result = rmse.get_square_root()
assert round(result, 5) == 2.43242
```