The Mathematical Intuition Behind the Curse of Dimensionality

The curse of dimensionality refers to the surprising phenomena that arise in high-dimensional data spaces, affecting areas such as distance metrics and model generalization in machine learning and data science. Understanding its mathematical foundations can provide deeper insights and improve performance in high-dimensional datasets. The concept was first introduced by Richard Bellman in 1961.