A study of the optimality of PCA under spectral sparsification
Share
Metadata
Show full item recordDate of publishing
2018Type of publication
conference paperSubject(s)
Abstract
Principal component analisys (PCA) is a data analysis technique for mapping points in Rn to a two or three dimensional space. This dimensionality reduction preserves the natural grouping of points and information of data.