GPR:基本的高斯过程回归库。 (需要Eigen3)-源码

上传者: 42099151 | 上传时间: 2021-09-07 09:46:17 | 文件大小: 116KB | 文件类型: ZIP
C++
GPR-基本高斯过程库 基本的高斯过程回归库。 (需要Eigen3) 特征 多元高斯过程回归 计算一个点的导数 计算某一点的不确定性 将高斯过程保存到文件中或从文件中加载 内核:白色,高斯,周期,有理二次,求和与乘积 内核的导数 似然函数:高斯对数似然(包括派生wrt。内核参数) 先验分布:高斯,反高斯,伽玛(包括采样,cdf和反cdf) 可以通过提供先验分布和众数来建立先验分布 入门 要设置库,请首先克隆git存储库 git clone https://github.com/ChristophJud/GPR.git GPR的建设是基于。 因此,导航到主目录GPR并创建一个构建目录。 mkdir build # create a build directory cd build ccmake .. # ccmake is an easy tool to set config pa

文件下载

资源详情

[{"title":"( 48 个子文件 116KB ) GPR:基本的高斯过程回归库。 (需要Eigen3)-源码","children":[{"title":"GPR-master","children":[{"title":"apps","children":[{"title":"GaussianProcessLearn.cpp <span style='color:#111;'> 4.84KB </span>","children":null,"spread":false},{"title":"CMakeLists.txt <span style='color:#111;'> 440B </span>","children":null,"spread":false},{"title":"GaussianProcessPredict.cpp <span style='color:#111;'> 3.50KB </span>","children":null,"spread":false}],"spread":true},{"title":"lib","children":[{"title":"GaussianProcess.cpp <span style='color:#111;'> 28.04KB </span>","children":null,"spread":false},{"title":"CMakeLists.txt <span style='color:#111;'> 371B </span>","children":null,"spread":false},{"title":"MatrixIO.cpp <span style='color:#111;'> 4.26KB </span>","children":null,"spread":false}],"spread":true},{"title":"CMakeLists.txt <span style='color:#111;'> 885B </span>","children":null,"spread":false},{"title":"LICENSE <span style='color:#111;'> 11.06KB </span>","children":null,"spread":false},{"title":"cmake","children":[{"title":"FindEigen3.cmake <span style='color:#111;'> 2.92KB </span>","children":null,"spread":false},{"title":"FindLAPACK.cmake <span style='color:#111;'> 6.20KB </span>","children":null,"spread":false},{"title":"GPRConfig.cmake <span style='color:#111;'> 472B </span>","children":null,"spread":false}],"spread":true},{"title":"README.md <span style='color:#111;'> 2.69KB </span>","children":null,"spread":false},{"title":"tests","children":[{"title":"GaussianLikelihoodTest.cpp <span style='color:#111;'> 11.02KB </span>","children":null,"spread":false},{"title":"InversionMethodsTest.cpp <span style='color:#111;'> 5.27KB </span>","children":null,"spread":false},{"title":"PeriodicKernelTest.cpp <span style='color:#111;'> 5.43KB </span>","children":null,"spread":false},{"title":"KernelDerivativeTest.cpp <span style='color:#111;'> 21.62KB </span>","children":null,"spread":false},{"title":"CMakeLists.txt <span style='color:#111;'> 574B </span>","children":null,"spread":false},{"title":"HighlyGeneralKernelTest.cpp <span style='color:#111;'> 4.80KB </span>","children":null,"spread":false},{"title":"LAPACKTest.cpp <span style='color:#111;'> 6.52KB </span>","children":null,"spread":false},{"title":"SumKernelTest.cpp <span style='color:#111;'> 5.85KB </span>","children":null,"spread":false},{"title":"MaximumLikelihoodTest2.cpp <span style='color:#111;'> 11.45KB </span>","children":null,"spread":false},{"title":"PosteriorProcessTest.cpp <span style='color:#111;'> 5.44KB </span>","children":null,"spread":false},{"title":"ProductKernelTest.cpp <span style='color:#111;'> 6.03KB </span>","children":null,"spread":false},{"title":"IOTest.cpp <span style='color:#111;'> 7.31KB </span>","children":null,"spread":false},{"title":"MaximumAPosterioriTest.cpp <span style='color:#111;'> 20.66KB </span>","children":null,"spread":false},{"title":"ScopeTest.cpp <span style='color:#111;'> 4.69KB </span>","children":null,"spread":false},{"title":"data","children":[{"title":"breathing3D.mat <span style='color:#111;'> 88.44KB </span>","children":null,"spread":false},{"title":"breathing1D.mat <span style='color:#111;'> 29.48KB </span>","children":null,"spread":false}],"spread":false},{"title":"GaussianProcessTest.cpp <span style='color:#111;'> 8.39KB </span>","children":null,"spread":false},{"title":"SparseInferenceTest.cpp <span style='color:#111;'> 15.49KB </span>","children":null,"spread":false},{"title":"PriorTest.cpp <span style='color:#111;'> 3.43KB </span>","children":null,"spread":false},{"title":"RationalQuadraticKernelTest.cpp <span style='color:#111;'> 6.85KB </span>","children":null,"spread":false}],"spread":false},{"title":"include","children":[{"title":"SparseLikelihood.h <span style='color:#111;'> 22.21KB </span>","children":null,"spread":false},{"title":"PriorUtils.h <span style='color:#111;'> 1.96KB </span>","children":null,"spread":false},{"title":"SparseGaussianProcess.h <span style='color:#111;'> 14.98KB </span>","children":null,"spread":false},{"title":"KernelFactory.h <span style='color:#111;'> 7.97KB </span>","children":null,"spread":false},{"title":"GaussianProcess.h <span style='color:#111;'> 10.35KB </span>","children":null,"spread":false},{"title":"CMakeLists.txt <span style='color:#111;'> 282B </span>","children":null,"spread":false},{"title":"KernelUtils.h <span style='color:#111;'> 3.38KB </span>","children":null,"spread":false},{"title":"LikelihoodUtils.h <span style='color:#111;'> 2.64KB </span>","children":null,"spread":false},{"title":"Likelihood.h <span style='color:#111;'> 12.35KB </span>","children":null,"spread":false},{"title":"MatrixIO.h <span style='color:#111;'> 918B </span>","children":null,"spread":false},{"title":"Prior.h <span style='color:#111;'> 25.90KB </span>","children":null,"spread":false},{"title":"GaussianProcessBase.h <span style='color:#111;'> 643B </span>","children":null,"spread":false},{"title":"GaussianProcessInference.h <span style='color:#111;'> 9.01KB </span>","children":null,"spread":false},{"title":"GaussianProcessITK.h <span style='color:#111;'> 4.00KB </span>","children":null,"spread":false},{"title":"LAPACKUtils.h <span style='color:#111;'> 3.11KB </span>","children":null,"spread":false},{"title":"Kernel.h <span style='color:#111;'> 37.27KB </span>","children":null,"spread":false}],"spread":false}],"spread":true}],"spread":true}]

评论信息

免责申明

【只为小站】的资源来自网友分享,仅供学习研究,请务必在下载后24小时内给予删除,不得用于其他任何用途,否则后果自负。基于互联网的特殊性,【只为小站】 无法对用户传输的作品、信息、内容的权属或合法性、合规性、真实性、科学性、完整权、有效性等进行实质审查;无论 【只为小站】 经营者是否已进行审查,用户均应自行承担因其传输的作品、信息、内容而可能或已经产生的侵权或权属纠纷等法律责任。
本站所有资源不代表本站的观点或立场,基于网友分享,根据中国法律《信息网络传播权保护条例》第二十二条之规定,若资源存在侵权或相关问题请联系本站客服人员,zhiweidada#qq.com,请把#换成@,本站将给予最大的支持与配合,做到及时反馈和处理。关于更多版权及免责申明参见 版权及免责申明