Unformatted text preview: be calculated otherwise than as euclidian distances, the distance from each vector to each other vector can be given here, size dlen x dlen. For example PDIST function can be used to calculate the distances: Dist = squareform(pdist(D,'mahal')); [alpha0] (scalar) initial step size, 0.5 by default [lambda0] (scalar) initial radius of influence, 3*max(std(D)) by default P (matrix) size dlen x odim, the projections Unknown values (NaN's) in the data: projections of vectors with unknown components tend to drift towards the center of the projection distribution. Projections of totally unknown vectors are set to unknown (NaN). See also SAMMON, PCAPROJ. [ SOM Toolbox online doc ]...
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This note was uploaded on 05/23/2010 for the course CS 245 taught by Professor Dunno during the Spring '10 term at Aarhus Universitet.
- Spring '10
- Machine Learning