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Description: 支持向量机学习中用到的用Matlab编写的工具箱。-support vector machines used in the study prepared by using Matlab toolbox.
Platform: |
Size: 1004113 |
Author: 明文 |
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Description: 1、工具箱:LS_SVMlab
Classification_LS_SVMlab.m - 多类分类
Regression_LS_SVMlab.m - 函数拟合
2、工具箱:OSU_SVM3.00
Classification_OSU_SVM.m - 多类分类
3、工具箱:stprtool\\svm
Classification_stprtool.m - 多类分类
4、工具箱:SVM_SteveGunn
Classification_SVM_SteveGunn.m - 二类分类
Regression_SVM_SteveGunn.m - 函数拟合
-a toolbox : LS_SVMlab Classification_LS_SVMlab.m-over classification Regression_LS_SVMlab.m-function fitting 2, toolbox : OSU_SVM3.00 Classification_OSU_SVM.m-over classification 3, toolbox : stprtool \\ svm Classification_stprtool.m-over category Categories 4, toolbox : SVM_SteveGunn Classification_SVM_SteveGun n.m-II classification Regression_SVM_SteveGunn.m-fitting function
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Size: 2697321 |
Author: 赵阳 |
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Description: 这里实现了基于四种SVM工具箱的分类与回归算法:
1、工具箱:LS_SVMlab
Classification_LS_SVMlab.m - 多类分类
Regression_LS_SVMlab.m - 函数拟合
2、工具箱:OSU_SVM3.00
Classification_OSU_SVM.m - 多类分类
3、工具箱:stprtool\\svm
Classification_stprtool.m - 多类分类
4、工具箱:SVM_SteveGunn
Classification_SVM_SteveGunn.m - 二类分类
Regression_SVM_SteveGunn.m - 函数拟合
更详细的相关函数说明请通过help命令查看!
Platform: |
Size: 2740501 |
Author: 杨愚根 |
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Description: 这里实现了四种SVM工具箱的分类与回归算法
1、工具箱:LS_SVMlab
Classification_LS_SVMlab.m - 多类分类
Regression_LS_SVMlab.m - 函数拟合
2、工具箱:OSU_SVM3.00
Classification_OSU_SVM.m - 多类分类
3、工具箱:stprtool\\svm
Classification_stprtool.m - 多类分类
4、工具箱:SVM_SteveGunn
Classification_SVM_SteveGunn.m - 二类分类
Regression_SVM_SteveGunn.m - 函数拟合
觉得好就帮我顶一下帖子,要不沉了!
Platform: |
Size: 232737 |
Author: fgqqd |
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Description: 用于非线性系统预测滤波的经典算法,由最小支持向量机算法创始人亲自编写。
Platform: |
Size: 995899 |
Author: 123456 |
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Description: 最小二乘支持向量机的代码包,包含对参数的优化过程,比较好用
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Size: 998181 |
Author: zhouweiqing |
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Description: LS_SVMlab工具箱,可以实现二分类、多分类和回归,内有详尽demo以及100多页的pdf使用手册,不懂支持向量机的可以通过改工具箱及手册很容易上手。
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Size: 995289 |
Author: yibeiweixi@126.com |
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Description: E:\课程资料\向量机 E:\课程资料\向量机\LS_SVMlab\LS_SVMlab\trainlssv.m
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Size: 3353 |
Author: gaobin2010 |
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Description: 支持向量机学习中用到的用Matlab编写的工具箱。-support vector machines used in the study prepared by using Matlab toolbox.
Platform: |
Size: 1003520 |
Author: 明文 |
Hits:
Description: 1、工具箱:LS_SVMlab
Classification_LS_SVMlab.m - 多类分类
Regression_LS_SVMlab.m - 函数拟合
2、工具箱:OSU_SVM3.00
Classification_OSU_SVM.m - 多类分类
3、工具箱:stprtool\svm
Classification_stprtool.m - 多类分类
4、工具箱:SVM_SteveGunn
Classification_SVM_SteveGunn.m - 二类分类
Regression_SVM_SteveGunn.m - 函数拟合
-a toolbox : LS_SVMlab Classification_LS_SVMlab.m-over classification Regression_LS_SVMlab.m-function fitting 2, toolbox : OSU_SVM3.00 Classification_OSU_SVM.m-over classification 3, toolbox : stprtool \ svm Classification_stprtool.m-over category Categories 4, toolbox : SVM_SteveGunn Classification_SVM_SteveGun n.m-II classification Regression_SVM_SteveGunn.m-fitting function
Platform: |
Size: 2697216 |
Author: 赵阳 |
Hits:
Description: 这里实现了基于四种SVM工具箱的分类与回归算法:
1、工具箱:LS_SVMlab
Classification_LS_SVMlab.m - 多类分类
Regression_LS_SVMlab.m - 函数拟合
2、工具箱:OSU_SVM3.00
Classification_OSU_SVM.m - 多类分类
3、工具箱:stprtool\svm
Classification_stprtool.m - 多类分类
4、工具箱:SVM_SteveGunn
Classification_SVM_SteveGunn.m - 二类分类
Regression_SVM_SteveGunn.m - 函数拟合
更详细的相关函数说明请通过help命令查看!-Here the realization of the four SVM toolbox based on the classification and regression algorithm: 1, Toolbox: LS_SVMlabClassification_LS_SVMlab.m- Multiclass Classification Regression_LS_SVMlab.m- function fitting 2, the toolbox: OSU_SVM3.00Classification_OSU_SVM.m- Multiclass Classification 3, Toolbox: stprtoolsvmClassification_stprtool.m- Multiclass Classification 4 toolbox: SVM_SteveGunnClassification_SVM_SteveGunn.m- II Category Regression_SVM_SteveGunn.m- function fitting a more detailed explanation of the correlation function through the help command to view!
Platform: |
Size: 2740224 |
Author: 杨愚根 |
Hits:
Description: 这里实现了四种SVM工具箱的分类与回归算法
1、工具箱:LS_SVMlab
Classification_LS_SVMlab.m - 多类分类
Regression_LS_SVMlab.m - 函数拟合
2、工具箱:OSU_SVM3.00
Classification_OSU_SVM.m - 多类分类
3、工具箱:stprtool\svm
Classification_stprtool.m - 多类分类
4、工具箱:SVM_SteveGunn
Classification_SVM_SteveGunn.m - 二类分类
Regression_SVM_SteveGunn.m - 函数拟合
觉得好就帮我顶一下帖子,要不沉了!
-Here to realize the four SVM toolbox Classification and Regression Algorithm 1, Toolbox: LS_SVMlabClassification_LS_SVMlab.m- Multiclass Classification Regression_LS_SVMlab.m- function fitting 2, the toolbox: OSU_SVM3.00Classification_OSU_SVM.m- Multiclass Classification 3, Toolbox : stprtoolsvmClassification_stprtool.m- Multiclass Classification 4, Toolbox: SVM_SteveGunnClassification_SVM_SteveGunn.m- II Category Regression_SVM_SteveGunn.m- function fitting to help me feel good on top of you post, or heavy!
Platform: |
Size: 232448 |
Author: fgqqd |
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Description: 用于非线性系统预测滤波的经典算法,由最小支持向量机算法创始人亲自编写。-Prediction filter for nonlinear systems of the classical algorithm, from the smallest support vector machine algorithm for the preparation of the founder himself.
Platform: |
Size: 995328 |
Author: 123456 |
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Description: 最小二乘支持向量机的代码包,包含对参数的优化过程,比较好用-Least squares support vector machine code package, include a parameter optimization process, comparative ease of use
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Size: 998400 |
Author: zhouweiqing |
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Description: LS_SVMlab.rar
Platform: |
Size: 995328 |
Author: 林立 |
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Description: 特别好,希望对大家有帮助。好好看看。肯定是有用的-Particularly good, I hope all of you help. A good look at. Is certainly useful
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Size: 995328 |
Author: svmgirl |
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Description: 基于最小二乘法的支持向量机可以用于分类,它比传统的支持向量机方法更省时,准确率更高-Based on least squares support vector machine can be used for classification, it is than the traditional support vector machine method is more time-saving, higher accuracy
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Size: 995328 |
Author: 赵林 |
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Description: 支持向量机matlab代码,用于分类和拟合-programme in matlab
Platform: |
Size: 995328 |
Author: Richard_wlc |
Hits:
Description: 工具箱:LS_SVMlab
Classification_LS_SVMlab.m - 多类分类
Regression_LS_SVMlab.m - 函数拟合-Toolbox: LS_SVMlab Classification_LS_SVMlab.m- multi-class classification Regression_LS_SVMlab.m- function fitting
Platform: |
Size: 1014784 |
Author: xianjun |
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Description: 工具箱:LS_SVMlab
Classification_LS_SVMlab.m - 多类分类
Regression_LS_SVMlab.m - 函数拟合
有大量程序
-so many matlab
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Size: 994304 |
Author: 豆 |
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