DocumentCode
3250800
Title
Optimal projections of high dimensional data
Author
Corchado, Emilio ; Fyfe, Colin
Author_Institution
Departamento de Ingenieria Civil, Burgos Univ., Spain
fYear
2002
fDate
2002
Firstpage
589
Lastpage
596
Abstract
In this paper, we compare two artificial neural network algorithms for performing Exploratory Projection Pursuit, a statistical technique for investigating data by projecting it onto lower dimensional manifolds. The neural networks are extensions of a network which performs Principal Component Analysis. We illustrate the technique on artificial data before applying it to real data.
Keywords
data structures; learning (artificial intelligence); neural nets; principal component analysis; Exploratory Projection Pursuit; Principal Component Analysis; artificial neural network; lower dimensional manifolds; neural networks; Artificial neural networks; Computational intelligence; Data mining; Joining processes; Mean square error methods; Negative feedback; Neurons; Nonlinear equations; Principal component analysis; Statistical analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Mining, 2002. ICDM 2003. Proceedings. 2002 IEEE International Conference on
Print_ISBN
0-7695-1754-4
Type
conf
DOI
10.1109/ICDM.2002.1184006
Filename
1184006
Link To Document