What is the curse of dimensionality, and how does it affect data?
Reviewed by Jason Burns, Editorial Steward · Last updated
The curse of dimensionality is the set of problems that arise when analyzing data in high-dimensional spaces: distances become less meaningful, data becomes sparse, and the number of samples needed for reliable learning grows rapidly with the number of features.