@conference {12851,
	title = {Choosing data vectors representing a huge data set. Kohonen{\textquoteright}s SOM applied to the Kefallinia erosion data.},
	booktitle = {1st International Conference on Environmental Research \& Assessment},
	year = {2003},
	abstract = {<p>We consider a large set of data comprising N=3422 data vectors, each containing observations on p=3 variables. We find for these data representative data vectors. We do it by employing the methodology of Kohonen{\textquoteright}s self-organizing maps. The found representative data vectors are called codebook vectors. In particular we analyze two collections (assemblages) of codebook vectors counting m=275 and m=120 elements. The quantity of the representation is measured by evaluating two errors: the quantization error q1 and the topological error q2. We show for our data that the magnitude of these errors depends on the way the original data were<br>standardized. After a thorough graphical analysis of the results we came to the conclusion that codebook vectors obtained from data standardized by range yield a little better representation as those do which were obtained from data standardized by variance. None of the representations is satisfactory from our point of view.</p>},
	author = {Bartkowiak, A. and Vassilopoulos, A. and Evelpidou, N.}
}
