HyperAI

Core Set Discovery

Core set discovery refers to the identification of the smallest training dataset in machine learning that can enable a supervised learning algorithm to achieve the same performance as when using the entire dataset. The goal is to improve algorithm efficiency by reducing the amount of training data while maintaining model performance. This method has significant application value in large-scale data processing, resource optimization, and accelerating model training.