Title :
A Mistake Application for Principal Component Analysis
Author :
Han, Run-chun ; Xiao, Ji-Xian
Author_Institution :
Sch. of Econ. & Manage., Hebei Polytech. Univ., Tangshan, China
Abstract :
When solving multivariate sample data, principal component analysis (PCA) can simplify the source, reduce the dimension of redundancies, and make the new variable uncorrelated, so it is widely utilized in multivariate statistical analysis. These years, however, some people apply the PCA to determine the weight of evaluation index system, even include the method in the textbook. This paper will clarify the unscientific method of valuing the weight in two ways.
Keywords :
principal component analysis; sampling methods; PCA; evaluation index system weight; mistake application; multivariate sample data; multivariate statistical analysis; principal component analysis; unscientific method; Conference management; Data processing; Mathematics; Physics computing; Principal component analysis; Psychology; Statistical analysis; Evaluation System; Principal Component Analysis; Weight;
Conference_Titel :
Information and Computing Science, 2009. ICIC '09. Second International Conference on
Conference_Location :
Manchester
Print_ISBN :
978-0-7695-3634-7
DOI :
10.1109/ICIC.2009.302
