High Dimensional means that the number of dimensions are staggeringly high — so high that calculations become extremely difficult. With high dimensional data, the number of features can exceed the number of observations. For example, microarrays, which measure gene expression, can contain tens of hundreds of samples.

What is considered a high dimensional data?

High dimensional data refers to a dataset in which the number of features p is larger than the number of observations N, often written as p >> N. ... A dataset could have 10,000 features, but if it has 100,000 observations then it's not high dimensional.

What is meant by higher dimensions?

“It is just a space where you can go up-down, left-right, ahead-back, but also in one other dimension, something like leftB-rightB,” he says. ... “It is a bit like having many arms, like an Indian god.”