# 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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Release files for nn-metrics 1.0.0
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