Update: Introducing UI support

What's New?

1. Intuitive User Interface
2. Redesigned layout for easy navigation.
3. Clear visual indicators for classification results.
4. Interactive elements to guide users through the process.

AI vs Human Text Classification with K-Fold Cross-Validation

Version 0.1.0: AI vs Human Text Classification with K-Fold Cross-Validation

Features

1. K-Fold Cross-Validation Implementation:

   • Added support for 5-Fold Cross-Validation to validate the performance of the Logistic Regression model.
   • Evaluates metrics like Accuracy, Precision, Recall, and ROC AUC for each fold.
   • Provides mean and standard deviation for all metrics to ensure model robustness.

2. Logistic Regression Optimization:

   • Trains the model with TF-IDF vectorized text features.
   • Final model trained on the full dataset after cross-validation.

Visualizations

• Histogram of Decision Function Scores:

  • A histogram visualizing decision scores and the classification decision boundary.

• Top Features for AI vs Human Classification:

  • Bar charts showing the top 10 positive (AI-indicative) and negative (Human-indicative) features.

• Precision-Recall Curve:

  • A plot demonstrating the trade-off between precision and recall for Logistic Regression.

Code Optimizations

• Streamlined preprocessing functions to clean text efficiently without external dependencies.
• Optimized hyperparameters for Logistic Regression for better performance during cross-validation.

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Getting Started

1. Clone the repository:

   git clone <repository-url>