Issue No. 02 - February (2002 vol. 24)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/34.982904
<p><b>Abstract</b>—Discriminants are often used in pattern recognition to separate clusters of points in some multidimensional “feature” space. This paper provides two fast and simple techniques for improving on the classification performance provided by Fisher's linear discriminant for two classes. Both of these methods are also extended to nonlinear decision surfaces through the use of Mercer kernels.</p>
Linear discriminant, classification.
T. Cooke, "Two Variations on Fisher's Linear Discriminant for Pattern Recognition," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 24, no. , pp. 268-273, 2002.