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IDA
1998
Springer

Fast Dimensionality Reduction and Simple PCA

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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.
Matthew Partridge, Rafael A. Calvo
Added 22 Dec 2010
Updated 22 Dec 2010
Type Journal
Year 1998
Where IDA
Authors Matthew Partridge, Rafael A. Calvo
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