高斯过程 回归

Author: Jarno Vanhatalo <Jarno.Vanhatalo@tkk.fi> Last modified: 2011-03-22 12:31:42 EET ----------------------------------------------------------------- GPstuff: Gaussian process models for Bayesian analysis V3.1.0 (r618) Maintainers: Jarno Vanhatalo <jarno.vanhatalo@tkk.fi> Aki Vehtari <aki.vehtari@tkk.fi> This software is distributed under the GNU General Public Licence (version 2 or later); please refer to the file Licence.txt, included with the software, for details. Table of contents: 1. INTRODUCTION 2. DOCUMENTATION AND DEMOS 3. INSTALLING THE TOOLBOX 4. USER QUIDE (VERY SHORT) 5. KNOWN PROBLEMS WITH INSTALLING SUITESPARSE AND SOLUTIONS TO THEM ------------------------------------------ 1. INTRODUCTION GPstuff is a collection of Matlab functions to build and analyze Bayesian models build over Gaussian processes. The toolbox is tested with Matlab 7.9 in 64bit Windows and Linux environments (it should work in the 32bit versions as well but they are not tested properly). 2. INSTALLING THE TOOLBOX Some of the functions in GPstuff are implemented using C in order to make the computations faster. In order to use these functions you need to compile them first. There are two ways to do that: 1) Basic installation without compactly supported covariance functions * Install the GPstuff package by running 'matlab_install' in this folder * With this option you are able to use all the other functions except for gpcf_ppcs* 2) Installation with compactly supported covariance functions Compactly supported (CS) covariance functions are functions that produce sparse covariance matrices (matrices with zero elements). To use these functions (gpcf_ppcs*) you need the sparse GP functionalities in GPstuff which are build over SuiteSparse toolbox by Tim Davis. To take full advantage of the CS covariance functions install GPstuff as follows: * First install SuiteSparse from: http://www.cise.ufl.edu/research/sparse/SuiteSparse/current/SuiteSparse/ Note! Install also Metis 4.0.1 as mentioned in the site under header "Other packages required:". Note2! There are problems with installing SuiteSparse in some architechtures. See the end of this document for known problems and solutions. * Install the GPstuff package: Run 'matlab_install( suitesparse_path )' in the present directory. Here suitesparse_path is a string telling the path to SuiteSparse package (for example, '/matlab/toolbox/SuiteSparse/'). Note! It is important that suitesparse_path is in right format. Include also the last '/' sign in it. In windows replace / by \. The function matlab_install compiles the mex-files and prints on the screen, which directories should be added to Matlab paths. 3. CONTENTS The packge contains the following subdirectories: diag dist gp mc misc optim Each folder contains Contents.m, which summarizes the functions in the folder. From the above 'gp' folder contains the main functionalities and demonstration programs. Other folders contain additional help functions. 4. USER QUIDE (VERY SHORT) It easiest to learn to use the package by running the demos. It is advisable to open the demo files in text editor and run them line by line. The demos are documented so that user can follow what happens on each line. The basic structure of the program is as follows. The program consist of separate blocks, which are: Gaussian process model structure (GP): This is a structure that contains all the model information (see gp_init) and information on, which inference scheme is used. GP structure contains covariance function structures (GPCF_*) and likelihood structures (LIKELIH_*). Covariance function structure (GPCF): This is a structure that contains all of the covariance function information (see e.g. gpcf_sexp). The structure contains the hyperparameter values, pointers to nested functions that are related to the covariance function (e.g. function to evaluate covariance matrix) and hyperprior structure. likelihood structure: This is a structure that contains all of the likelihood function information (see e.g. likelih_probit). The structure contains the likelihood parameter values and pointers to nested functions that are related to the likelihood function (e.g. log likelihood and its derivatives). Inference utilities: Inference utilities consist of functions that are needed to make the posterior inference and predictions. These include, among others, GP_E - Evaluate conditional log posterior density GP_G - Evaluate gradient of conditional log posterior EP_PRED - Predictions with Gaussian Process EP GP_MC - Markov chain Monte Carlo sampling 5. KNOWN PROBLEMS WITH INSTALLING SUITESPARSE AND SOLUTIONS TO THEM There are some problems with installing SuiteSparse for 64bit Linux, Matlab 7.8 (or newer). The problem can be fixed as follows - Compiling SuiteSparse seems to finish allright. However, when running demos you will end up in segmentation fault. - The problem occurs with CHOLMOD, UMFPACK, and SPQR packages and can be prevented with the following steps: * Open file SuiteSparse/CHOLMOD/MATLAB/cholmod_make.m * Go to the line 46 * Replace the following lines (46) if (~isempty (strfind (computer, '64'))) (47) % 64-bit MATLAB (48) d = '-largeArrayDims' ; (49) end with the following ones if (~isempty (strfind (computer, '64'))) % 64-bit MATLAB d = '-largeArrayDims' ; % The next three lines are added by jarno.vanhatalo@iki.fi (-09). % These options are needed for some reason in Matlab 7.8 or newer. if v >= 7.8 d = [d ' -DLONG -D''LONGBLAS=UF_long''']; end end * Open file SuiteSparse/SPQR/MATLAB/spqr_make.m * Go to the line 58 * Replace the following lines (58) if (is64) (59) % 64-bit MATLAB (60) d = '-largeArrayDims' ; (61) end with the following ones if (is64) % 64-bit MATLAB d = '-largeArrayDims' ; % The next three lines are added by jarno.vanhatalo@iki.fi (-09). % These options are needed for some reason in Matlab 7.8 or newer. if v >= 7.8 d = [d ' -DLONG -D''LONGBLAS=UF_long''']; end end * Open file SuiteSparse/UMFPACK/MATLAB/umfpack_make.m * Go to the line 21 * replace the following lines (21) if (~isempty (strfind (computer, '64'))) (22) d = ' -largeArrayDims' ; (23) end with the following ones v = getversion ; % Added by jarno.vanhatalo@iki.fi (-09). if (~isempty (strfind (computer, '64'))) d = ' -largeArrayDims' ; % The next three lines are added by jarno.vanhatalo@iki.fi (-09). % These options are needed for some reason in Matlab 7.8 or newer. if v >= 7.8 d = [d ' -DLONG -D''LONGBLAS=UF_long''']; end end