文件列表:

gpclass\augvec.m (1041, 1997-11-27)
gpclass\driverm.m (4544, 1997-11-27)
gpclass\final_pred.m (3570, 1997-11-27)
gpclass\getPmat.m (1168, 1997-11-27)
gpclass\getmat.m (1369, 1997-11-27)
gpclass\getmclasses.m (2291, 1997-11-27)
gpclass\getmode.m (4518, 1997-11-27)
gpclass\getnoise_sp.m (1498, 1997-11-27)
gpclass\invAxB.m (1446, 1997-11-27)
gpclass\invIpSN.m (1563, 1997-11-27)
gpclass\licence.txt (17976, 1997-11-26)
gpclass\makepredm.m (3304, 1997-11-27)
gpclass\mgrad.m (5377, 1997-11-27)
gpclass\minvg.m (1118, 1997-11-27)
gpclass\mpot.m (4303, 1997-11-27)
gpclass\mprintf.m (1212, 1997-11-27)
gpclass\oilpipe.dat (47554, 1997-11-16)
gpclass\oilpipe_demo.m (6047, 1997-11-27)
gpclass\pak.m (1168, 1997-11-27)
gpclass\putmclass.m (2172, 1997-11-27)
gpclass\scg.m (6544, 1997-11-28)
gpclass\threshold.m (1387, 1997-11-27)
gpclass\trlog.m (1110, 1997-11-27)
gpclass\unpak.m (1087, 1997-11-27)
gpclass\vec2mitheta.m (1165, 1997-11-27)
gpclass\vhmcm.m (6381, 1997-11-27)
gpclass (0, 2008-02-22)

% Matlab code for Gaussian Processes for Classification: % GPCLASS version 0.2 10 Nov 97 % Copyright (c) David Barber and Christopher K I Williams (1997) % This program is free software; you can redistribute it and/or modify % it under the terms of the GNU General Public License as published by % the Free Software Foundation; either version 2 of the License, or % any later version. % % This program is distributed in the hope that it will be useful, % but WITHOUT ANY WARRANTY; without even the implied warranty of % MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the % GNU General Public License for more details. % % You should have received a copy of the GNU General Public License % along with this program; if not, write to the Free Software % Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA. The main routines are mpot.m ====== calculates the log probability of being in a hyperparameter state mgrad.m ======= calculates the derivate of the log probability of being in a hyperparameter state makepredm.m =========== finds the means and covariance matrix for the activation posteriror for all the test and training points. driverm.m ========= once the data has been set up, this program calls the MAP routine or the HMC routine as appropriate getmode.m ========= finds the laplace solution and associated parameters final_pred.m ============ calculates the mean predictions scg.m ===== scaled conjugate gradient optimiser vhmcm.m ======= Hybrid Monte Carlo routine vec2mitheta.m ============= converts a vector representation of the hyperparameters to a matrix threshold.m =========== thresholds values above a specified limit trlog.m ======= calculates the trace(log(A)) = log(det(A)) - useful if det(A) is very large ( or very small) putmclass.m =========== stores the mean and covariance matrix of the posterior on file mprintf.m ========= simple matrix print routine getmat.m ======== simple routine that loads in a matrix getnoise_sp.m ============= calculates the noise matrix

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