A central issue in principal component analysis (PCA) is choosing the number of principal components to be retained. By interpreting PCA as density estimation, this paper shows ho...
An important problem in principal component analysis (PCA) is the estimation of the correct number of components to retain. PCA is most often used to reduce a set of observed vari...
We study dimensionality reduction or feature selection in text document categorization problem. We focus on the first step in building text categorization systems, that is the cho...
Abstract. This paper proposes a new algorithm for the automatic segmentation of motion data from a humanoid soccer playing robot that allows feedforward neural networks to generali...
Rawichote Chalodhorn, Karl F. MacDorman, Minoru As...
Most dimension reduction techniques produce ordered coordinates so that only the first few coordinates need be considered in subsequent analyses. The choice of how many coordinate...