SVR与RVR
所属分类：matlab编程
开发工具：matlab
文件大小：30KB
下载次数：14
上传日期：2019-12-28 11:43:47
上 传 者：
MR.TanGG
说明： 用于支持向量回归（SVR）和启示向量回归（RVR）分析以及交叉验证，以评估预测能力。
(It is used for support vector regression (SVR) and Revelation vector regression (RVR) analysis and cross validation to evaluate prediction ability.)
文件列表:
SVR2\RVR (0, 2018-10-21)
SVR2\RVR\prt_machine_rvr.m (2058, 2018-10-21)
SVR2\RVR\prt_rvr.m (17457, 2018-10-21)
SVR2\RVR\RVR_LOOCV.m (4068, 2018-10-21)
SVR2\RVR\RVR_NFolds.m (5244, 2018-10-21)
SVR2\RVR\RVR_W_Permutation.m (1696, 2018-10-21)
SVR2\RVR\W_Calculate_RVR.m (2383, 2018-10-21)
SVR2\RVR\W_Calculate_RVR_SGE.m (389, 2018-10-21)
SVR2\SVR (0, 2018-10-21)
SVR2\SVR\CorrFilter_SVR_LOOCV.m (3185, 2018-10-21)
SVR2\SVR\NBS (0, 2018-10-21)
SVR2\SVR\NBS\Random_Merge_100.m (671, 2018-10-21)
SVR2\SVR\NBS\Random_w2p_100_script.m (690, 2018-10-21)
SVR2\SVR\NBS\Random_w2p_100_script_2.m (691, 2018-10-21)
SVR2\SVR\NBS\Significance_NBS.m (3100, 2018-10-21)
SVR2\SVR\Regression_Prediction_Sig.m (755, 2018-10-21)
SVR2\SVR\Regression_W_Sig.m (684, 2018-10-21)
SVR2\SVR\Regression_W_Sig_100.m (730, 2018-10-21)
SVR2\SVR\Regression_W_Sig_100_ForSGE.m (743, 2018-10-21)
SVR2\SVR\Regression_W_Sig_100_ForSGE_parent.m (489, 2018-10-21)
SVR2\SVR\Regression_W_Sig_100_SGE.m (1311, 2018-10-21)
SVR2\SVR\Regression_W_Sig_200.m (730, 2018-10-21)
SVR2\SVR\Regression_W_Sig_ForSGE.m (926, 2018-10-21)
SVR2\SVR\Regression_W_Sig_ForSGE_parent.m (216, 2018-10-21)
SVR2\SVR\Regression_W_Sig_MaximumStatistics.m (916, 2018-10-21)
SVR2\SVR\Regression_W_Sig_SGE.m (1096, 2018-10-21)
SVR2\SVR\SVR.m~ (4930, 2018-10-21)
SVR2\SVR\SVR_LOOCV.m (3865, 2018-10-21)
SVR2\SVR\SVR_LOOCV_ForSGE.m (241, 2018-10-21)
SVR2\SVR\SVR_NFolds.m (4959, 2018-10-21)
SVR2\SVR\SVR_NFolds_Avg.m (839, 2018-10-21)
SVR2\SVR\SVR_NFolds_ForSGE.m (719, 2018-10-21)
SVR2\SVR\SVR_NFolds_Repeat.m (2116, 2018-10-21)
SVR2\SVR\SVR_Permutation.m (1772, 2018-10-21)
SVR2\SVR\SVR_W_Permutation.m (1432, 2018-10-21)
SVR2\SVR\SVR_W_Permutation_2.m (789, 2018-10-21)
SVR2\SVR\SVR_W_Permutation_3.m (876, 2018-10-21)
SVR2\SVR\SVR_W_Permutation_4.m (922, 2018-10-21)
SVR2\SVR\W_Calculate_SVR.m (2278, 2018-10-21)
... ...
# Pattern_Regression_Matlab
Matlab code for support vector regression (SVR) and revelance vector regression (RVR) analysis with cross validation to evaluate the prediction power.
Also see the codes here https://github.com/ZaixuCui/Pattern_Regression_Clean.
Citing our related paper will be greatly appreciated if you use these codes.
```Zaixu Cui, Gaolang Gong; The effect of machine learning regression algorithms and sample size on individualized behavioral prediction with functional connectivity features, NeuroImage, Volume 178, Pages 622-637```
```Zaixu Cui, Mengmeng Su, Liangjie Li, Hua Shu, Gaolang Gong; Individualized Prediction of Reading Comprehension Ability Using Gray Matter Volume, Cerebral Cortex, Volume 28, Issue 5, 1 May 2018, Pages 1656“1672, https://doi.org/10.1093/cercor/bhx061```
```Zaixu Cui, Zhichao Xia, Mengmeng Su, Hua Shu, Gaolang Gong, 2016. Disrupted white matter connectivity underlying developmental dyslexia: A machine learning approach. Hum Brain Mapp 37, 1443-1458.```
Revelance vector Regression (RVR) is implemented using PRoNTo (http://www.mlnl.cs.ucl.ac.uk/pronto/).
The function prt_rvr.m and prt_machine_rvr.m are functions of this software.
Support vector regression (SVR) is implemented using LIBSVM (https://www.csie.ntu.edu.tw/~cjlin/libsvm/).
Copyright (c) Zaixu Cui, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University.
Contact information: zaixucui@gmail.com
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