Description: 使用最小二乘支持向量机对多维pyrim数据进行回归，需要下载最小二乘支持向量机工具箱。-use of least squares support vector machines for multidimensional data pyrim return need to download least squares support vector machines toolbox. Platform: |
Size: 2433 |
Author:肖勇 |
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Description: 最小二乘支持向量机MATLAB实现源代码，可以用于模式识别以及回归，DEMOCLASS是使用方法示例-least squares support vector machines MATLAB source code, can be used for pattern recognition and regression, DEMOCLASS example is the use of Platform: |
Size: 712192 |
Author:刘霞 |
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Description: 使用最小二乘支持向量机对多维pyrim数据进行回归，需要下载最小二乘支持向量机工具箱。-use of least squares support vector machines for multidimensional data pyrim return need to download least squares support vector machines toolbox. Platform: |
Size: 2048 |
Author:肖勇 |
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Description: 最小二乘支持向量机MATLAB实现源代码，可以用于模式识别以及回归，DEMOCLASS是使用方法示例-least squares support vector machines MATLAB source code, can be used for pattern recognition and regression, DEMOCLASS example is the use of Platform: |
Size: 716800 |
Author:刘霞 |
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Description: 最小二乘支持向量机的matlab工具包，包括源程序和使用说明-Least squares support vector machines matlab toolkit, including the source and use Platform: |
Size: 224256 |
Author:mountyang |
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Description: 最小二乘支持向量机的一个小程序，非常简单，也很耗用-Least Squares Support Vector Machines, a small program, very simple and consumption Platform: |
Size: 84992 |
Author:huangkang |
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Description: 这是一篇关于最小二乘支持向量机的文章，主要是应用最小二乘支持向量机来对文本进行分类！-This is an article on least squares support vector machines article, mainly the application of least squares support vector machines to classify the text! Platform: |
Size: 204800 |
Author:李萍 |
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Description: 最小二乘支持向量机的matlab工具箱，包含几乎所有常用的支持向量机应用函数。-Least squares support vector machines matlab toolbox, including almost all commonly used applications of support vector machine function. Platform: |
Size: 194560 |
Author:alfred_woo |
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Description: c语言例题程序，还有最小二乘法支持向量机的MATLAB调试测试运行-Example programs c language, as well as least squares support vector machines to run MATLAB Debugging and Testing Platform: |
Size: 40960 |
Author:小马 |
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Description: A differential pulse stripping method for the simultaneous determination of lead and tin is proposed. The
procedure involves accumulation with dissolving of lead and tin on a hanging mercury drop electrode
(HMDE), followed by oxidation of dissolve lead and tin by voltammetric scan using differential pulse
modulation. The optimum experimental conditions are: 0.2 mol L1 HNO3, accumulation potential of
900 mV versus Ag/AgCl, accumulation time of 200 s, scan rate of 20 mV s1 and pulse height of
80 mV. Lead and tin peak currents were observed in the same potential region at about 400 mV. The
simultaneous determination of lead and tin by using voltammetry is a difficult problem in analytical
chemistry, due to voltammogram interferences. The resolution of mixture of lead and tin by the application
of least-squares support vector machines (LS-SVM) Platform: |
Size: 126976 |
Author:bahman |
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Description: This book focuses on Least Squares Support Vector Machines (LS-SVMs) which are reformulations to standard SVMs. LS-SVMs are closely related to regularization networks and Gaussian processes but additionally emphasize and exploit primal-dual interpretations from optimization theory. The authors explain the natural links between LS-SVM classifiers and kernel Fisher discriminant analysis. Platform: |
Size: 29890560 |
Author:lichen |
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Description: A hybrid least squares support vector
machines and GMDH approach for river
fl ow forecasting-This paper proposes a novel hybrid forecasting model, which combines the group
method of data handling (GMDH) and the least squares support vector machine
(LSSVM), known as GLSSVM. The GMDH is used to determine the useful input vari-
ables for LSSVM model and the LSSVM model which works as time series forecasting. 5
In this study the application of GLSSVM for monthly river fl ow forecasting of Selangor
and Bernam River are investigated. The results of the proposed GLSSVM approach
are compared with the conventional artifi cial neural network (ANN) models, Autoregres-
sive Integrated Moving Average (ARIMA) model, GMDH and LSSVM models using the
long term observations of monthly river fl ow discharge. The standard statistical, the 10
root mean square error (RMSE) and coe ffi cient of correlation (R) are employed to eval-
uate the performance of various models developed. Experiment result indicates that
the hybrid model was powerful tools to mo Platform: |
Size: 1467392 |
Author: |
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Description: 最小二乘隐空间支持向量机
王玲 薄列峰 刘芳 焦李成
!
在隐空间中采用最小二乘损失函数$提出了 最 小 二 乘 隐 空 间 支 持 向 量 机#0*&**52H 8
同 隐 空 间 支 持 向
量机#&**52H 一样$最小二乘隐空间支持向量机不需 要 核 函 数 满 足 正 定 条 件$从 而 扩 展 了 支 持 向 量 机 核 函 数 的
选择范围
8
由于采用了最小二乘损失函数$最小二乘隐空间支持向量机产生的优 化 问 题 为 无 约 束 凸 二 次 规 划$这 比
隐空间支持向量机产生的约束凸二次规划更易求解
8
仿真实验结果表明所提算法在 计 算 时 间 和 推 广 能 力 上 较 隐 空
间支持向量机存在一定的优势
-In the hidden space, using the least square loss function space $ proposed least squares support vector machine hidden# 0* &** 52H 8
Space with the implicit support to the
The amount of machine# &** 52H $ as an implicit least squares support vector machines do not need space to meet definite conditions $ kernel function extends SVM kernel function
Range of options
8
As a result of an implicit least squares loss function space $ least squares support vector machine optimization problem arising from the unconstrained convex quadratic programming for the $ than
Hidden space support vector machines produce more constrained convex quadratic programming solver
8
Simulation results show that the proposed method in computation time and the ability to promote a more implicit empty
Between the support vector machine there is a certain advantage Platform: |
Size: 161792 |
Author:lux |
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Description: 英文原版的最小二乘支持向量机1.5版使用说明，包含每个函数的详细使用说明-English original 1.5 version of least squares support vector machines for use, contains detailed instructions for each function Platform: |
Size: 772096 |
Author:张泽宇 |
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Description: 对目标函数的松弛变量引入一个参数μ，优化基本的最小二乘一类支持向量机算法。同样是解决线性问题，避免了二次规划的复杂问题(A parameter min is introduced into the relaxation variable of the objective function, and the basic least squares support vector machines algorithm is optimized. It also solves the linear problems and avoids the complex problems of the two programming) Platform: |
Size: 279552 |
Author:菲尔德
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Search - least squares support vector machines