Visualizing the full extent of the curse of dimensionality

Visualizing the True Extent of the Curse of Dimensionality

Using the Monte Carlo method to visualize the behavior of observations with very large numbers of features

Think of a dataset, made of some number of observations, each observation having N features. If you convert all features to a numeric representation, you could say that each observation is a point in an N-dimensional space.

When N is low, the relationships between points are just what you would expect intuitively. But sometimes …

behavior curse-of-dimensionality data science dataset dimensionality dimensionality-reduction features machine learning monte-carlo-method numbers observation representation the curse of dimensionality true