Normalized Root Mean Squared Error (NRMSE) Calculation

[amirshamaei]

🚀 Feature
Normalized Root Mean Squared Error (NRMSE) Calculation
Motivation
Calculating the Normalized Root Mean Squared Error (NRMSE) is a widely used metric in various fields, such as image processing, signal analysis, and machine learning. However, the absence of a built-in NRMSE function in our current toolkit poses challenges for users who require this metric for evaluating model performance and accuracy.

Pitch
I propose the addition of a native NRMSE calculation function to our toolkit, streamlining the process for users and enhancing the overall user experience. This feature would empower users to easily assess the performance of their models, fostering better-informed decision-making and refining their models for optimal results.

Alternatives
While users can currently implement custom code to calculate NRMSE, having a dedicated function within the toolkit would eliminate the need for additional development efforts. This would save time and resources for users who frequently utilize NRMSE in their work.

Additional context
The inclusion of NRMSE as a built-in feature aligns with our commitment to providing comprehensive tools for users across diverse domains. This enhancement would contribute to a more robust and user-friendly toolkit, catering to the needs of our community and ensuring a smoother workflow for those relying on NRMSE for their evaluations.

[github-actions]

Hi! thanks for your contribution!, great first issue!