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 03-nov-2024