readme.progs

来自「gaussian procession 原程序,用于解决分类问题,有兴趣可以看看」· PROGS 代码 · 共 110 行

%            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