Various phenomena arising from analyzing/organizing data in high-dimensional spaces

When increasing the dimensionality, the volume of the space increases so much so that the available data becomes sparse; i.e. data density takes an exponential hit.

Implications

Exponential growth in number of examples needed to maintain sample density- This implies that for a given dataset, there is limit to the number of features above which the performance of a learning system will degrade.

bias-variance tradeoff