Optimized Weather Classification using XGBoost & Genetic Algorithm

Weather classification is a challenging multi-class problem that requires robust models and well-tuned hyperparameters. While XGBoost is known for its high performance on structured data, its effectiveness strongly depends on proper hyperparameter tuning.

To address this, we leveraged a Genetic Algorithm (GA) to automatically search for optimal configurations, significantly improving model generalization and performance.