Description: 相关向量机(RVM)的matlab源程序，包含快速算法，内含代码使用说明。
RVM采取是与支持向量机相同的函数形式稀疏概率模型，对未知函数进行预测或分类。 优点：
(1) 不仅仅输出预测目标量的点估计值,还可以输出预测值的分布.
(2) 使用更少数量的支持向量,从而显著减少输出目标量预测值的计算时间.
(3) RVM不需要估计过多的参数.
(4) RVM对是否满足Mercer 定理的核函数没有限制,适应性更好.
-Relevance Vector Machine (RVM) of the matlab source code, including the fast algorithm that contains the code instructions. RVM to support vector machines with the same function form of sparse probabilistic model to predict the unknown function, or classification. Advantages: (1) The goal is not only the amount of the output forecast point estimates, but also the distribution of the output forecast. (2) use less number of support vectors, thus significantly reduce the amount of predictive value of the output goal of computing time. (3) RVM does not require too many parameters estimated. (4) RVM on whether to satisfy Mercer' s theorem is no limit on nuclear function, adaptability and better. Platform: |
Size: 157696 |
Author:何创新 |
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Description: 关联向量机的硕士博士论文，关联向量机是支持向量机的发展，开发工具主要是matlab-Associated with the master s thesis vector machines, relevance vector machine is the development of support vector machines, development tools, mainly matlab
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Size: 39526400 |
Author:chenyt |
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Description: 相关向量机，在人工智能领域较新的应用，希望大家看一下-Relevance vector machine, new applications in the field of artificial intelligence, I hope you look at
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Size: 206848 |
Author:suwangyan |
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Description: 相关向量机的电力负荷预测，在人工智能领域较新的应用，希望大家看一下-Relevance vector machine, new applications in the field of artificial intelligence, I hope you look at
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Size: 162816 |
Author:suwangyan |
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Description: 关于相关向量机的学习，在人工智能领域较新的应用，希望大家看一下-Relevance vector machine, new applications in the field of artificial intelligence, I hope you look at
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Size: 223232 |
Author:suwangyan |
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Description: 稀疏贝叶斯学习和相关向量回归，大家可以看一下，人工智能中的应用-Relevance vector machine, new applications in the field of artificial intelligence, I hope you look at...
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Author:suwangyan |
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Description: 关于相关向量机的pdf文档，一个是原作者的文档，一个是中国学者的学习文档，通俗易懂，是学习相关向量机的很好的资料，另有基于rvm的预测程序。-Pdf documents on relevance vector machine, a documentation of the original author, a Chinese scholar s study documents, easy to understand, to learn the information of relevance vector machine, and another based on the forecast program rvm. Platform: |
Size: 1683456 |
Author:梁永亮 |
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Description: 相关向量机，的极大似然估计文件与SB2配合使用，可以进行扩展-Relevance vector machine, maximum likelihood estimation file with SB2 used in conjunction, can be extended Platform: |
Size: 1024 |
Author:ytf |
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Description: This m file implements the bottom-up relevance vector machine with multivariate outputs, proposed in.-This m file implements the bottom-up relevance vector machine with multivariate outputs, proposed in. Platform: |
Size: 2048 |
Author:hamed |
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Description: A Comprehensive Sparse Learning Package-Descriptions: Six sparse algorithms are implemented in this package. They are
1) SVM
2) L1-norm SVM
a) Linear Programming SVM
b) SC-SVM
3) L0-norm SVM
4) RVM (Relevance Vector Machine)
5) SPC (Sparse Probit Classifier) Platform: |
Size: 794624 |
Author:陈超 |
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Description: 相关向量机(RVM)的matlab源程序，包含快速算法，内含代码使用说明。 RVM采取是与支持向量机相同的函数形式稀疏概率模型，对未知函数进行预测或分类。 优点： (1) 不仅仅输出预测目标量的点估计值,还可以输出预测值的分布. (2) 使用更少数量的支持向量,从而显著减少输出目标量预测值的计算时间. (3) RVM不需要估计过多的参数. (4) RVM对是否满足Mercer 定理的核函数没有限制,适应性更好-Relevance Vector Machine (RVM) of the matlab source code, including fast algorithm that contains code for use. RVM support vector machine is taken the same functional form sparse probabilistic model to predict the unknown function or classification. Advantages: (1) is not only the amount of output predicted target point estimates, but also the distribution of predicted values can be output. (2) using a smaller number of support vectors, thereby significantly reducing the output target amount predicted value calculation time. (3) RVM does not require excessive parameter estimation. (4) RVM meets Mercer theorem on the kernel function is not limited, and better adaptability Platform: |
Size: 160768 |
Author:小芝麻 |
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Description: 支持向量机是用于分类与回归的技术。由于其自身的诸多缺点，如无法获得概率输出，需要估计一个误
差参数C，以及必须使用Mercer 核函数等。相关向量机算法，克服了SVM 上述缺点，RVM 能获得与SVM 相比拟的推
广性能，并且更为稀疏。在此基础上，文中介绍了一种RVM 回归用于分类的新分类方法，用RVRC 来表示。并通过
实验证明了它的可行性。-Support vector machines for classification and regression techniques. Due to its many shortcomings, such as the probability that the output can not be obtained, need to estimate an error parameter C, and the need to use Mercer kernel function and so on. Relevance vector machine algorithm to overcome these shortcomings of SVM, RVM and SVM can be obtained comparable to promote performance and more sparse. On this basis, the paper introduces a RVM regression was used to classify new classification method, RVRC to represent. And through experiments proved its feasibility. Platform: |
Size: 198656 |
Author:小芝麻 |
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Search - relevance vector machine