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PRTools User Guide



Train mapping between two representations

     [W,V] = MAPSD(S,D,P,Q)

 S Dataset, source representation, typically high-dimensional
 D Dataset, destination representation, typically low-dimensional
 P Non-linearity parameter for W between 0 and 1, default 0.01
 Q Non-linearity parameter for V between 0 and 1, default 0.01

 W Mapping, such that D = S*W
 V Mapping, such that S = D*V


This mapping is useful to generalise mappings like MDS and TSNEM such  that they can be applied to new datasets. Once by such routines a proper  low-dimensional representation D is found for the original dataset S then  W can be applied to find an approximate representation D2 of a similar to  S source representation S2 by D2 = S2*W.

See also

datasets, mappings, mds, tsnem,

PRTools Contents

PRTools User Guide

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