登录
首页 » matlab » gpml-matlab-v1.3-2006-09-08

gpml-matlab-v1.3-2006-09-08

于 2020-02-26 发布
0 338
下载积分: 1 下载次数: 3

代码说明:

说明:  高斯过程(GP)模型中推理和预测的实现。它实现了在《Rasmussen & Williams:机器学习的高斯过程》(麻省理工学院出版社,2006)和《Nickisch & Rasmussen:二进制高斯过程分类的近似》(JMLR, 2008)中讨论的算法。该函数的优点在于灵活性、简单性和可扩展性。该函数具有一定的灵活性,首先通过定义均值函数和协方差函数来确定遗传算法的性质。其次,它允许指定不同的推理过程,如精确推理和期望传播(EP)。第三,它允许指定似然函数,如高斯函数或拉普拉斯函数(用于回归)和累积逻辑函数(用于分类)。简单性是通过一个简单的函数和紧凑的代码实现的。可扩展性是通过模块化设计来保证的,允许为已经相当广泛的推理方法、均值函数、协方差函数和似然函数库轻松添加扩展。(Gaussian Processes for Machine Learning , the MIT press, 2006 and Nickisch & Rasmussen: Approximations for Binary Gaussian Process Classification , JMLR, 2008. The strength of the function lies in its flexibility, simplicity and extensibility. The function is flexible as firstly it allows specification of the properties of the GP through definition of mean function and covariance functions. Secondly, it allows specification of different inference procedures, such as e.g. exact inference and Expectation Propagation (EP). Thirdly it allows specification of likelihood functions e.g. Gaussian or Laplace (for regression) and e.g. cumulative Logistic (for classification). Simplicity is achieved through a single function and compact code.)

文件列表:

gpml-matlab, 0 , 2006-09-08
gpml-matlab\README, 3741 , 2006-09-08
gpml-matlab\doc, 0 , 2006-03-29
gpml-matlab\doc\classification.html, 34439 , 2006-03-27
gpml-matlab\doc\alg31.gif, 43172 , 2005-11-07
gpml-matlab\doc\style.css, 77 , 2006-01-30
gpml-matlab\doc\alg32.gif, 34064 , 2005-11-07
gpml-matlab\doc\index.html, 3349 , 2006-03-29
gpml-matlab\doc\alg35.gif, 66673 , 2006-02-10
gpml-matlab\doc\alg36.gif, 32226 , 2006-02-10
gpml-matlab\doc\alg51.gif, 60084 , 2006-01-31
gpml-matlab\doc\alg52.gif, 41085 , 2006-02-10
gpml-matlab\doc\figepp.gif, 17875 , 2006-03-10
gpml-matlab\doc\figepp2.gif, 23299 , 2006-03-10
gpml-matlab\doc\figlapp.gif, 17854 , 2006-03-09
gpml-matlab\doc\figlapp2.gif, 25557 , 2006-03-09
gpml-matlab\doc\regression.html, 16598 , 2006-03-29
gpml-matlab\doc\figl1.gif, 21386 , 2005-10-26
gpml-matlab\doc\alg21.gif, 31996 , 2005-10-26
gpml-matlab\doc\sparse-approx.html, 7738 , 2006-03-29
gpml-matlab\doc\fig2d.gif, 36772 , 2006-03-14
gpml-matlab\doc\fig2de1.gif, 35364 , 2006-03-14
gpml-matlab\doc\figlf.gif, 16078 , 2006-03-27
gpml-matlab\doc\fig2de2.gif, 42683 , 2006-03-14
gpml-matlab\doc\fig2de3.gif, 38483 , 2006-03-14
gpml-matlab\doc\fig2dl1.gif, 34059 , 2006-03-14
gpml-matlab\doc\fig2dl2.gif, 40431 , 2006-03-14
gpml-matlab\doc\fig2dl3.gif, 38375 , 2006-03-14
gpml-matlab\doc\figl.gif, 6109 , 2006-03-27
gpml-matlab\doc\figlm.gif, 16712 , 2006-03-27
gpml-matlab\gpml, 0 , 2006-09-08
gpml-matlab\gpml\binaryEPGP.m, 7565 , 2006-09-08
gpml-matlab\gpml\binaryLaplaceGP.m, 7940 , 2006-05-10
gpml-matlab\gpml\Contents.m, 2206 , 2006-04-07
gpml-matlab\gpml\Copyright, 775 , 2006-02-09
gpml-matlab\gpml\gprSRPP.m, 2963 , 2006-03-30
gpml-matlab\gpml\minimize.m, 8995 , 2006-09-08
gpml-matlab\gpml\solve_chol.c, 1236 , 2006-02-09
gpml-matlab\gpml\solve_chol.m, 991 , 2006-02-08
gpml-matlab\gpml\sq_dist.c, 1931 , 2006-02-08
gpml-matlab\gpml\sq_dist.m, 2186 , 2006-03-09
gpml-matlab\gpml\covMatern5iso.m, 1221 , 2006-03-24
gpml-matlab\gpml\covRQiso.m, 1486 , 2006-09-08
gpml-matlab\gpml\covMatern3iso.m, 1206 , 2006-03-24
gpml-matlab\gpml\covSEiso.m, 1349 , 2006-04-07
gpml-matlab\gpml\Makefile, 131 , 2006-03-29
gpml-matlab\gpml\covFunctions.m, 4136 , 2006-05-15
gpml-matlab\gpml\gpr.m, 2811 , 2006-03-27
gpml-matlab\gpml\covSEard.m, 1569 , 2006-03-24
gpml-matlab\gpml\covProd.m, 2582 , 2006-04-06
gpml-matlab\gpml\covLINone.m, 984 , 2006-03-27
gpml-matlab\gpml\covSum.m, 2400 , 2006-03-20
gpml-matlab\gpml\covNoise.m, 1065 , 2006-03-24
gpml-matlab\gpml\covNNone.m, 1778 , 2006-03-24
gpml-matlab\gpml\covRQard.m, 1660 , 2006-09-08
gpml-matlab\gpml\covPeriodic.m, 1085 , 2006-04-07
gpml-matlab\gpml\covLINard.m, 1046 , 2006-03-24
gpml-matlab\gpml\covConst.m, 758 , 2006-03-24
gpml-matlab\gpml-demo, 0 , 2006-03-29
gpml-matlab\gpml-demo\Contents.m, 791 , 2006-03-27
gpml-matlab\gpml-demo\data_6darm.mat, 22768 , 2006-02-27
gpml-matlab\gpml-demo\data_boston.mat, 57040 , 2006-03-29
gpml-matlab\gpml-demo\demo_ep_2d.m, 7012 , 2006-03-29
gpml-matlab\gpml-demo\demo_ep_usps.m, 6130 , 2006-03-29
gpml-matlab\gpml-demo\demo_gparm.m, 8178 , 2006-03-29
gpml-matlab\gpml-demo\demo_gprsparse.m, 6511 , 2006-03-29
gpml-matlab\gpml-demo\demo_laplace_2d.m, 7257 , 2006-03-29
gpml-matlab\gpml-demo\demo_laplace_usps.m, 6134 , 2006-03-29
gpml-matlab\gpml-demo\demo_gpr.m, 9382 , 2006-03-29

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论

0 个回复

  • Thres_ent
    Segmentation function for matlab : this fucntion convert an intensity image to a binary image by using Entropy-based method.
    2010-09-30 15:34:01下载
    积分:1
  • BER_simulation_with_matlab
    误码率仿真原理推导睡眠以及相应的matlab程序(BER simulation schematic derivation of sleep and the corresponding matlab program)
    2013-08-03 23:47:42下载
    积分:1
  • 3
    说明:  matlab编程环境下噪声信号的产生(噪声信号产生的matlab源代码)(creating noise signals )
    2011-12-12 14:34:22下载
    积分:1
  • 苏金明《Matlab工具箱应用》
    贝叶斯网络工具箱(FullBNT-1.0.4)使用说明(Bayesian Network Toolbox (FullBNT-1.0.4) Instructions for use)
    2021-03-31 13:19:09下载
    积分:1
  • Paper1
    DESIGN OF A NEURAL PREDICTIVE CONTROLLER FOR NONHOLONOMIC MOBILE ROBOT BASED ON POSTURE IDENTIFIER
    2015-01-06 04:51:50下载
    积分:1
  • meachnical-fault-diagnosis
    讲述了机械故障诊断中一些理论知识,如现在常用的HHT,对初学者有帮助。(Tells the story of some mechanical fault diagnosis theory of knowledge, such as the now commonly used HHT, help for beginners.)
    2013-11-24 10:32:09下载
    积分:1
  • 1
    说明:  《普林斯顿科学文库2-天遇混沌与稳定性的起源》 《普林斯顿科学文库2-天遇混沌与稳定性的起源》(&quot Princeton Science Library 2- day event of the origin of chaos and stability,&quot &quot Princeton Science Library 2- day event of the origin of chaos and stability,&quot )
    2010-04-20 11:33:28下载
    积分:1
  • MUSIC-TRANSFORM(Two-Tigers)
    产生两只老虎乐曲,并进行了谐波叠加,模拟声音(To produce two tigers music, and harmonic superposition, analog sound)
    2013-01-13 00:15:02下载
    积分:1
  • 029861723HOS_MIMO
    这是一个基于高阶统计量的盲信号分离算法,便于大家参考。(This is a higher-order statistics based on blind signal separation algorithms for easy reference.)
    2016-11-14 12:52:00下载
    积分:1
  • kalmanfilter
    maple写的基本kalman算法,可以做入门参考理解(maple write basic kalman algorithm, can be understood to do entry-reference)
    2008-02-28 16:44:59下载
    积分:1
  • 696516资源总数
  • 106914会员总数
  • 0今日下载