A fast and simple algorithm for approximately calculating the principal components (PCs) of a data set and so reducing its dimensionality is described. This Simple Principal Compo...
Abstract. Principal component analysis (PCA) and its dual—principal coordinate analysis (PCO)—are widely applied to unsupervised dimensionality reduction. In this paper, we sho...
In this paper we present a novel method for reducing false positives in breast mass detection. Our approach is based on using the Two-Dimensional Principal Component Analysis (2DPC...
This paper presents algorithms for efficiently computing the covariance matrix for features that form sub-windows in a large multidimensional image. For example, several image proc...
—Dimensionality reduction is essential in text mining since the dimensionality of text documents could easily reach several tens of thousands. Most recent efforts on dimensionali...