nn-metrics

Name	nn-metrics JSON
Version	1.0.0 JSON
	download
home_page	https://github.com/arif-x/nn-metrics
Summary	A collection of neural network machine learning error metrics.
upload_time	2024-03-29 14:17:03
maintainer	None
docs_url	None
author	Ariffudin
requires_python	None
license	MIT
keywords	nn neural-network metrics nn-metrics
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

            # Example Usage
```
# Import the required functions from your package
from nn_metrics.metrics import (
    mean_absolute_percentage_error,
    mean_absolute_error,
    mean_squared_error,
    root_mean_squared_error,
    binary_cross_entropy,
    categorical_correntropy,
    sparse_categorical_crossentropy
)

# Example usage:
actual = [10, 20, 30, 40, 50]
predicted = [12, 18, 28, 41, 48]

# Calculate and print error metrics
print("Mean Absolute Percentage Error (MAPE):", mean_absolute_percentage_error(actual, predicted))
print("Mean Absolute Error (MAE):", mean_absolute_error(actual, predicted))
print("Mean Squared Error (MSE):", mean_squared_error(actual, predicted))
print("Root Mean Squared Error (RMSE):", root_mean_squared_error(actual, predicted))
```


            

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