Fast Dimensionality Reduction and Simple PCA

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 Components Analysis (SPCA) method was used for dimensionality reduction of two high-dimensional image databases, one of handwritten digits and one of handwritten Japanese characters. It was tested and compared with other techniques. On both databases SPCA shows a fast convergence rate compared with other methods and robustness to the reordering of the samples.

• Type: Journal
• Year: 1998
• Where: IDA
• Authors: Matthew Partridge, Rafael A. Calvo
• Keywords: Handwritten Japanese Characters, IDA 1998, Information Technology, Principal Components, Simple Principal Components