Enhancement: Added Permutation Importance Visualization for Fraud Detection

[PrasDev4]

Pull Request for PyVerse 💡

Requesting to submit a pull request to the PyVerse repository.

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Issue Title

Enhancement: Added Permutation Importance Visualization for Fraud Detection

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Info about the Related Issue

What's the goal of the project?
The aim is to provide an interactive visualization of feature importance using permutation techniques, enhancing model interpretability and aiding in fraud detection insights.

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Name

Prasanna Devireddy

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GitHub ID

@PrasDev4

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Email ID

[email protected]

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Identify Yourself

SWOC Contributor

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Closes

Closes: #1138

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Describe the Add-ons or Changes You've Made

Added a new function to calculate and plot permutation importance.
This enhancement intertwines model insights with visualization to facilitate interpretability, providing an interactive visualization for feature importance in fraud detection models.

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Type of Change

Select the type of change:

• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Code style update (formatting, local variables)
• Breaking change (fix or feature that would cause existing functionality to not work as expected)
• This change requires a documentation update

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How Has This Been Tested?

The enhancement was tested with the provided fraud detection dataset.
The visualization was validated for accuracy using existing model metrics to ensure robust and meaningful insights.

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Checklist

Please confirm the following:

• My code follows the guidelines of this project.
• I have performed a self-review of my own code.
• I have commented my code, particularly wherever it was hard to understand.
• I have made corresponding changes to the documentation.
• My changes generate no new warnings.
• I have added things that prove my fix is effective or that my feature works.
• Any dependent changes have been merged and published in downstream modules.

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