Title :
Optimal projections of high dimensional data
Author :
Corchado, Emilio ; Fyfe, Colin
Author_Institution :
Departamento de Ingenieria Civil, Burgos Univ., Spain
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;
Conference_Titel :
Data Mining, 2002. ICDM 2003. Proceedings. 2002 IEEE International Conference on
Print_ISBN :
0-7695-1754-4
DOI :
10.1109/ICDM.2002.1184006
