GAMOS v1.0.1 – Initial Public Release

This is the first official release of GAMOS (Game-Theoretic Adaptive Minority Oversampling Strategy).

🔬 GAMOS is a novel oversampling algorithm that strategically generates synthetic samples for imbalanced datasets using game-theoretic reasoning and adaptive optimization.

📦 What's Included

• Full implementation of the GAME_GEN class
• Scikit-learn compatible fit_resample() method
• Feature-weighted noise injection
• Adaptive payoff-based sample optimization
• PCA and standardization support
• Built-in diversity and quality filtering mechanisms
• Minimal working example in examples/
• requirements.txt for dependency management