Adaptive Machine Learning: Dynamic Model Switching for Improved Accuracy Across Varying Dataset Sizes

A novel approach to dynamically switch between machine learning models, such as Random Forest and XGBoost, based on dataset characteristics to optimize predictive accuracy.