RT Conference Proceedings T1 A study of the optimality of PCA under spectral sparsification A1 Mercado, Sergio A1 Villagra, Marcos A2 Universidad Nacional de Asunción - Facultad Politécnica AB 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. YR 2018 FD 2018 LK http://hdl.handle.net/20.500.14066/3730 UL http://hdl.handle.net/20.500.14066/3730 LA eng NO CONACYT – Consejo Nacional de Ciencia y Tecnología DS MINDS@UW RD 29-mar-2024