Dimensionality reduction, or dimension reduction, is the transformation of data from a high-dimensional space into a low-dimensional space so that the low-dimensional representation retains some meaningful properties of the original data, ideally close to its intrinsic dimension.
Dimension Reduction is most likely to appear on 数据科学家 job descriptions where we found it mentioned 1.5 percent of the time.