School of Statistics - Interactive Classification Dashboards

Welcome to the Interactive Classification Dashboards project! This repository contains a set of tools designed to help users understand the core concepts of binary classification in machine learning through hands-on, visual interaction.

🚀 About This Project

🌐 Live Demos

• Direct Classification Dashboard
• Inverse Classification Dashboard

This project provides two distinct interactive dashboards:

1. Direct Classification Dashboard (direct_classifier.html) : This tool allows you to generate a synthetic 2D dataset for two classes. You can adjust the class separation and data spread (standard deviation) to see how these parameters affect the performance of a Gaussian Naive Bayes classifier. The dashboard visualizes:

   • The generated data points.
   • The resulting ROC curve and its Area Under the Curve (AUC).
   • Key performance metrics (Accuracy, Precision, Recall, etc.).
   • A detailed confusion matrix.

2. Inverse Classification Dashboard (inverse_classifier.html) : This tool works in reverse. Instead of generating data, you directly manipulate the values of the confusion matrix (True Positives, False Positives, True Negatives, and False Negatives). The application then simulates a distribution of classifier scores that would lead to your specified matrix and visualizes the resulting metrics, ROC curve, and score distribution. This provides a unique, intuitive way to understand the relationships between the confusion matrix and other performance indicators.

📂 Project Structure

The project has been organized into a clean and maintainable structure:

.
├── direct_classifier.html
├── inverse_classifier.html
├── LICENSE
├── README.md
└── src
    ├── assets
    │   └── logo.jpg
    ├── css
    │   ├── inverse_style.css
    │   └── style.css
    └── js
        ├── direct_classifier.js
        └── inverse_classifier.js

• direct_classifier.html: The main page for the direct classification tool.
• inverse_classifier.html: The main page for the inverse classification tool.
• src/: Contains all source assets.
  • assets/: Stores static assets like the project logo.
  • css/: Contains the stylesheets for the HTML pages.
  • js/: Contains the JavaScript logic for each interactive dashboard.
• LICENSE: The project's license file.
• README.md: This file.

🛠️ How to Use

1. Clone this repository to your local machine.
2. Open either direct_classifier.html or inverse_classifier.html in your web browser.
3. No local server is needed! All the logic is self-contained in the HTML, CSS, and JavaScript files.

Interact with the sliders and controls on each page to explore the concepts of classification.

📄 License

This project is distributed under the terms of the license specified in the LICENSE file.