Discrimination by means of components that are orthogonal in the data space
✍ Scribed by Henk A. L. Kiers
- Publisher
- John Wiley and Sons
- Year
- 1997
- Tongue
- English
- Weight
- 174 KB
- Volume
- 11
- Category
- Article
- ISSN
- 0886-9383
No coin nor oath required. For personal study only.
✦ Synopsis
Krzanowski (J. Chemometrics, 9, 509 (1995)
) proposed a method for obtaining so-called orthogonal canonical variates (henceforth called components) for discrimination purposes. In contrast with ordinary discriminant analysis, this method employs components that are orthogonal in the original data space. These components are derived in a successive way, thus optimizing discrimination of a component given the previously extracted components. Two alternative procedures are proposed to extract the desired number of components simultaneously, yielding a better overall discrimination. The simultaneous approaches are applied to the same two data sets as analysed by Krzanowski, as well as to Anderson's Iris data, and a comparison of discriminatory quality of the solutions is presented.