DocumentCode
3274166
Title
Applications of Principal Components Methods
Author
Pop, Horia F. ; Frentiu, Militon
Author_Institution
Dept. of Comput. Sci., Babes-Bolyai Univ., Cluj-Napoca, Romania
fYear
2008
fDate
8-10 Nov. 2008
Firstpage
103
Lastpage
109
Abstract
Multivariate statistical methods for the analysis of large quantities of data have been applied to problem solving in different domains during the last decades. This paper summarizes the main points of the principal components analysis (PCA) method and its robust fuzzy alternatives, and describes a few applications highlighting the practical usefulness of this approach.
Keywords
data analysis; fuzzy set theory; principal component analysis; software metrics; data quantity analysis; fuzzy set theory; multivariate statistical method; principal components analysis method; software metrics; Application software; Clustering algorithms; Computer science; Data mining; Fuzzy sets; Mathematics; Principal component analysis; Problem-solving; Robustness; Statistical analysis; Education; Fuzzy Sets; Principal Components Analysis; Software metrics; Software projects;
fLanguage
English
Publisher
ieee
Conference_Titel
Complexity and Intelligence of the Artificial and Natural Complex Systems, Medical Applications of the Complex Systems, Biomedical Computing, 2008. CANS '08. First International Conference on
Conference_Location
Targu Mures, Mures
Print_ISBN
978-0-7695-3621-7
Type
conf
DOI
10.1109/CANS.2008.20
Filename
5231494
Link To Document