en:tools:mlssvr
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en:tools:mlssvr [2017/04/20 14:08] pzczxs |
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| - | =====Multi-output Least-Squares Support Vector Regression Machine (MLS-SVR)===== | ||
| - | ====Introduction==== | ||
| - | Multi-output regression aims at learning a mapping from a multivariate input feature space to a multivariate output space. Despite its potential usefulness, the standard formulation of the least-squares support vector regression machine (LS-SVR) [1][2] cannot cope with the multi-output case. The usual procedure is to train multiple independent LS-SVR, thus disregarding the underlying (potentially nonlinear) cross relatedness among different outputs. | ||
| - | To address this problem, inspired by the multi-task learning methods (such as [3]), Xu et. al. [4] proprosed a novel approach, Multi-output LS-SVR (MLS-SVR), in multi-output setting. MLSSVR is a MATLAB implementation of MLS-SVR with the more efficient training algorithm in [4]. | ||
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| - | ====Programming Language==== | ||
| - | MATLAB | ||
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| - | ====Source Codes==== | ||
| - | https://github.com/pzczxs/MLSSVR | ||
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| - | ====Citation Information==== | ||
| - | If you find this toolbox useful, please cite MLS-SVR as follows: | ||
| - | *Shuo Xu, Xin An, Xiaodong Qiao, Lijun Zhu, and Lin Li, 2013. [[http://dx.doi.org/10.1016/j.patrec.2013.01.015|Multi-Output Least-Squares Support Vector Regression Machines]]. //Pattern Recognition Letters//, Vol. 34, No. 9, pp. 1078-1084. ''{{xushuo:papers:mls-svm.pdf|PDF}}'' | ||
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| - | ====References==== | ||
| - | -C. Saunders, A. Gammerman, and V. Vovk, 1998. Ridge Regression Learning Algorithm in Dual Variables. //Proceedings of the 15th International Conference on Machine Learning (ICML)//, pp. 515-521. | ||
| - | -Johan A. K. Suyken, Tony van Gestel, Jos de Brabanter, Bart de Moor, and Joos Vandewalle, 2002. Least-Squares Support Vector Machines. World Scientific Pub. Co. | ||
| - | -Theodoros Evgeniou and Massimiliano Pontil, 2004. Regularized Multi-Task Learning. //Proceedings of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD)//, pp. 109-117. | ||
| - | -Shuo Xu, Xin An, Xiaodong Qiao, Lijun Zhu, and Lin Li, 2013. [Multi-Output Least-Squares Support Vector Regression Machines](http://doi.org/10.1016/j.patrec.2013.01.015). //Pattern Recognition Letters//, Vol. 34, No. 9, pp. 1078-1084. | ||
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| - | ~~DISCUSSION~~ | ||
en/tools/mlssvr.1492668512.txt.gz · 最后更改: 2017/04/20 14:08 由 pzczxs