文件名称:gpml-matlab-v3.6-2015-07-07
介绍说明－－下载内容均来自于网络，请自行研究使用
这是一个高斯过程回归和分类工具箱，功能非常齐全，可以为解决高斯过程相关的问题提供很多帮助- GAUSSIAN PROCESS REGRESSION AND CLASSIFICATION Toolbox version 3.6
for GNU Octave 3.2.x and Matlab 7.x
Copyright (c) by Carl Edward Rasmussen and Hannes Nickisch, 2015-07-07.
0) HOW TO READ
==============
If you want to get started without further delay, then read section 1) below
and jump right to the examples in doc/index.html.
1) ABOUT THESE PROGRAMS
=======================
This collection of matlab programs implements and demonstrates some of the
algorithms described in
a) the book by Rasmussen and Williams: Gaussian Processes for Machine Learning ,
the MIT Press 2006, in
b) the article by Nickisch and Rasmussen: Approximations for Binary Gaussian
Process Classification , JMLR 2008, in
c) the article by Candela and Rasmussen: A Unifying View of Sparse Approximate
Gaussian Process Regression , JMLR 2005, in
d) the paper by Murray, Adams and Mackay: Elliptical slice sampling ,
AISTATS 2010, in
e) the report by Neal: Anneale
for GNU Octave 3.2.x and Matlab 7.x
Copyright (c) by Carl Edward Rasmussen and Hannes Nickisch, 2015-07-07.
0) HOW TO READ
==============
If you want to get started without further delay, then read section 1) below
and jump right to the examples in doc/index.html.
1) ABOUT THESE PROGRAMS
=======================
This collection of matlab programs implements and demonstrates some of the
algorithms described in
a) the book by Rasmussen and Williams: Gaussian Processes for Machine Learning ,
the MIT Press 2006, in
b) the article by Nickisch and Rasmussen: Approximations for Binary Gaussian
Process Classification , JMLR 2008, in
c) the article by Candela and Rasmussen: A Unifying View of Sparse Approximate
Gaussian Process Regression , JMLR 2005, in
d) the paper by Murray, Adams and Mackay: Elliptical slice sampling ,
AISTATS 2010, in
e) the report by Neal: Anneale
(系统自动生成,下载前可以参看下载内容)
下载文件列表
gpml-matlab-v3.6-2015-07-07\.octaverc
...........................\Copyright
...........................\cov
...........................\...\covADD.m
...........................\...\covConst.m
...........................\...\covCos.m
...........................\...\covDiscrete.m
...........................\...\covEye.m
...........................\...\covFITC.m
...........................\...\covGaborard.m
...........................\...\covGaboriso.m
...........................\...\covGrid.m
...........................\...\covLIN.m
...........................\...\covLINard.m
...........................\...\covLINiso.m
...........................\...\covLINone.m
...........................\...\covMask.m
...........................\...\covMaternard.m
...........................\...\covMaterniso.m
...........................\...\covNNone.m
...........................\...\covNoise.m
...........................\...\covPERard.m
...........................\...\covPeriodic.m
...........................\...\covPeriodicNoDC.m
...........................\...\covPERiso.m
...........................\...\covPoly.m
...........................\...\covPPard.m
...........................\...\covPPiso.m
...........................\...\covPref.m
...........................\...\covProd.m
...........................\...\covRQard.m
...........................\...\covRQiso.m
...........................\...\covScale.m
...........................\...\covSEard.m
...........................\...\covSEfact.m
...........................\...\covSEiso.m
...........................\...\covSEisoU.m
...........................\...\covSEvlen.m
...........................\...\covSM.m
...........................\...\covSum.m
...........................\covFunctions.m
...........................\doc
...........................\...\changelog
...........................\...\checkmark.png
...........................\...\demoClassification.m
...........................\...\demoGrid.m
...........................\...\demoRegression.m
...........................\...\f1.gif
...........................\...\f2.gif
...........................\...\f3.gif
...........................\...\f4.gif
...........................\...\f5.gif
...........................\...\f6.gif
...........................\...\f7.gif
...........................\...\f8.gif
...........................\...\f9.png
...........................\...\gpml_randn.m
...........................\...\index.html
...........................\...\manual.pdf
...........................\...\README
...........................\...\style.css
...........................\...\usageClassification.m
...........................\...\usageCov.m
...........................\...\usageLik.m
...........................\...\usageMean.m
...........................\...\usagePrior.m
...........................\...\usageRegression.m
...........................\...\usageSampling.m
...........................\gp.m
...........................\inf
...........................\...\infEP.m
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...........................\...\infFITC.m
...........................\...\infFITC_EP.m
...........................\...\infFITC_Laplace.m
...........................\...\infGrid.m
...........................\...\infGrid_Laplace.m
...........................\...\infKL.m
...........................\...\infLaplace.m
...........................\...\infLOO.m
...........................\...\infMCMC.m
...........................\...\infPrior.m
...........................\...\infVB.m
...........................\infMethods.m
...........................\lik
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...........................\...\likGamma.m
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...........................\...\likGaussWarp.m
...........................\...\likGumbel.m
...........................\...\likInvGauss.m
...........................\...\likLaplace.m
...........................\...\likLogistic.m
...........................\...\likMix.m