https://github.com/dms-codes/root-mean-squared-error

https://github.com/dms-codes/root-mean-squared-error

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• Host: GitHub
• URL: https://github.com/dms-codes/root-mean-squared-error
• Owner: dms-codes
• Created: 2024-12-07T02:22:08.000Z (about 1 month ago)
• Default Branch: main
• Last Pushed: 2024-12-07T02:26:24.000Z (about 1 month ago)
• Last Synced: 2024-12-07T03:21:31.873Z (about 1 month ago)
• Language: Python
• Size: 0 Bytes
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Root Mean Squared Error (RMSE) Calculation

This file demonstrates two ways to calculate the Root Mean Squared Error (RMSE) between two lists of values:

1. **Manual Calculation:** 

   - The `root_mean_squared_error` function calculates the RMSE directly by:

     - Checking for equal lengths of input lists.

     - Calculating the squared difference between corresponding values.

     - Summing the squared errors.

     - Calculating the mean of the squared errors.

     - Taking the square root of the mean squared error.

2. **Using scikit-learn:**

   - The `calculate_rmse` function leverages the `mean_squared_error` function from the scikit-learn library for efficient and concise RMSE calculation. 

     - It calculates the Mean Squared Error (MSE) using the scikit-learn function.

     - Then, it computes the square root of the MSE to obtain the RMSE.

## Example Usage

Both functions can be used as follows:

```python

actual = [2, 3, 5, 5, 9]

calculated = [3, 3, 8, 7, 6]

# Manual Calculation

rmse_manual = root_mean_squared_error(actual, calculated) 

print(f"Root Mean Squared Error (Manual): {rmse_manual}")

# Using scikit-learn

rmse_sklearn = calculate_rmse(actual, calculated)

print(f"Root Mean Squared Error (scikit-learn): {rmse_sklearn}")