📊 Precision-Recall Explorer for Business

Unveiling the Dynamics of Precision and Recall

Welcome to the Metrics Explorer – an interactive Shiny app designed to demystify the world of precision and recall for business stakeholders. Explore it here.

Key Features

1. Confusion Matrix Playground:

   • Visualize the interplay between precision and recall on a dynamic confusion matrix.
   • Explore the impact of tweaking these metrics on True Positives, True Negatives, False Positives, and False Negatives.

2. Performance Breakdown:

   • Get a closer look at your model's performance with key metrics:
     • Successful Predictions (True Positives) – the wins.
     • Accurate Non-events (True Negatives) – the silent guardians.
     • False Alarms (False Positives) – the surprises.
     • Missed Opportunities (False Negatives) – the near-misses.

3. Metrics in Plain Language:

   • Understand the metrics in business terms:
     • True Positives (TP): Successful Predictions.
     • True Negatives (TN): Accurate Non-events.
     • False Positives (FP): False Alarms.
     • False Negatives (FN): Missed Opportunities.

Your Business, Your Story

• Tailored Scenarios: Customize discussions to fit your business context.
• Use Case Integration: Whether it's loan default prediction or customer churn, see how precision and recall play out in your unique scenario.

How to Use

1. Clone or Download:

   • Clone the repository or download the ZIP file to get started.

2. Run Locally:

   • Open the Shiny app in RStudio or your preferred environment.

3. Interact and Learn:

   • Adjust the sliders for total sample, proportion of actual positives, precision, and recall.
   • Witness how changes impact the confusion matrix and key performance metrics.

Why Metrics Explorer?

Data Science often hits a "communication wall" when explaining model thresholds. This app breaks that wall by:

• Translating Jargon: Replaces TP/FP/TN/FN with business-friendly terms like "Wins" and "Surprises."
• Interactive Simulation: Let stakeholders "feel" the trade-off by moving sliders for precision and recall.
• Contextual Discussion: Ideal for "What-If" sessions regarding loan defaults, medical screening, or customer churn.

Contribute

• Issues and Contributions: If you find a bug or have an idea for improvement, open an issue or submit a pull request.

License

This project is licensed GNU GENERAL PUBLIC LICENSE.