DD_tools: lpdd

LPDD Linear programming distance data description

         W = LPDD(X,NU,S,DTYPE,P)
 
 One-class classifier put into a linear programming framework. From
 the data X the distance matrix is computed (using distance DTYPE,
 see myproxm for the possibilities). The distances are then
 transformed using a sigmoidal transformation (with parameter S,
 see the function dissim) and on this the linear machine is
 trained. The parameter NU gives the possible error on the target
 class.

 This function is basically a wrapper around dlpdd. See dd_ex2 to
 see how it works.

See also: myproxm dissim dlpdd dd_ex2 

@inproceedings{Pekalska2002,
	author = {Pekalska, E. and Tax, D.M.J. and Duin, R.P.W.},
	title = {One-class {LP} classifier for dissimilarity representations},
	booktitle = {Advances in Neural Information Processing Systems},
	year = {2003},
	pages = {},
  editor =       {S.~Becker and S.~Thrun and K.~Obermayer},
  volume =       {15},
  publisher = {MIT Press: Cambridge, MA}
}



Copyright: D.M.J. Tax, D.M.J.Tax@prtools.org
Faculty EWI, Delft University of Technology
P.O. Box 5031, 2600 GA Delft, The Netherlands