登录
首页 » matlab » SVM-matlab

SVM-matlab

于 2013-11-17 发布 文件大小:3846KB
0 257
下载积分: 1 下载次数: 39
我要下载

代码说明：

  经典SVM算法matlab程序,用于多种利用MATLAB对数据进行SVM仿真的实验。(Classical SVM algorithm matlab program for a variety of SVM data using MATLAB simulation experiments.)

文件列表：

经典SVM算法matlab程序
.....................\svm
.....................\...\binomial.m,371,1997-09-19
.....................\...\centrefig.m,144,1998-05-01
.....................\...\cmap.mat,1728,1997-08-13
.....................\...\Contents.m,1105,1998-08-07
.....................\...\Examples
.....................\...\........\Classification
.....................\...\........\..............\iris1v23.mat,2696,1997-09-28
.....................\...\........\..............\iris2v13.mat,2696,1997-09-28
.....................\...\........\..............\iris3v12.mat,2696,1997-09-28
.....................\...\........\..............\linsep.mat,672,1997-11-06
.....................\...\........\..............\nlinsep.mat,712,1997-11-06
.....................\...\........\Regression
.....................\...\........\..........\example.mat,744,1997-11-07
.....................\...\........\..........\sinc.mat,1056,1997-08-20
.....................\...\........\..........\titanium.mat,1096,1997-09-27
.....................\...\newsvm.zip,76534,2001-10-26
.....................\...\nobias.m,457,1998-08-06
.....................\...\Optimiser
.....................\...\.........\Makefile,27,2001-10-11
.....................\...\.........\pr_loqo.c,16731,2001-10-11
.....................\...\.........\pr_loqo.h,2388,2001-10-11
.....................\...\.........\qp.c,7245,2001-10-11
.....................\...\.........\qp.dll,49152,2001-10-26
.....................\...\qp.dll,49152,2001-10-26
.....................\...\htm" target=_blank>README,2642,2001-10-12
.....................\...\softmargin.m,312,1998-04-21
.....................\...\svc.m,2687,1998-08-21
.....................\...\svcerror.m,837,1998-08-21
.....................\...\svcinfo.m,1228,1998-03-10
.....................\...\svcoutput.m,973,1998-04-21
.....................\...\svcplot.m,3109,2001-10-12
.....................\...\svdatanorm.m,1299,1998-06-23
.....................\...\svkernel.m,2608,2001-10-11
.....................\...\svr.m,3982,1998-08-21
.....................\...\svrerror.m,1203,1998-08-21
.....................\...\svroutput.m,711,1998-04-15
.....................\...\svrplot.m,1823,1998-02-13
.....................\...\svtol.m,401,1998-08-21
.....................\...\uiclass.m,5386,1997-11-18
.....................\...\uiclass.mat,12592,1997-11-18
.....................\...\uiregress.m,5627,1997-09-27
.....................\...\uiregress.mat,11640,1998-10-12
.....................\SVM_luzhenbo
.....................\............\Classification_stprtool.m,2351,2007-03-15
.....................\............\Classification_SVM_SteveGunn.m,1542,2007-03-15
.....................\............\codelssvm.m,4125,2003-02-21
.....................\............\initlssvm.m,4042,2003-02-21
.....................\............\kernel_matrix.m,2182,2003-02-21
.....................\............\lssvmMATLAB.m,3534,2003-02-21
.....................\............\LS_SVMlab
.....................\............\.........\AFE.m,2738,2003-02-21
.....................\............\.........\bay_errorbar.m,5785,2003-02-21
.....................\............\.........\bay_initlssvm.m,2003,2003-02-21
.....................\............\.........\bay_lssvm.m,10345,2003-02-21
.....................\............\.........\bay_lssvmARD.m,8187,2003-02-21
.....................\............\.........\bay_modoutClass.m,9358,2003-02-21
.....................\............\.........\bay_optimize.m,5977,2003-02-21
.....................\............\.........\bay_rr.m,4178,2003-02-21
.....................\............\.........\buffer.mc,164,2005-04-15
.....................\............\.........\changelssvm.m,5632,2003-02-21
.....................\............\.........\Classifacation_fourfaults.m,2897,2009-02-24
.....................\............\.........\Classification_fourfaults_4000_6000.m,4697,2009-03-02
.....................\............\.........\Classification_LS_SVMlab.m,2618,2009-05-15
.....................\............\.........\code.m,4245,2005-04-15
.....................\............\.........\codedist_bay.m,2118,2003-02-21
.....................\............\.........\codedist_hamming.m,756,2003-02-21
.....................\............\.........\codedist_loss.m,2018,2003-02-21
.....................\............\.........\codelssvm.m,4125,2003-02-21
.....................\............\.........\code_ECOC.m,5197,2003-02-21
.....................\............\.........\code_MOC.m,550,2003-02-21
.....................\............\.........\code_OneVsAll.m,364,2003-02-21
.....................\............\.........\code_OneVsOne.m,555,2003-02-21
.....................\............\.........\Contents.m,32,2003-03-20
.....................\............\.........\crossvalidate.m,8174,2003-02-21
.....................\............\.........\deltablssvm.m,1886,2003-02-21
.....................\............\.........\democlass.m,3369,2003-02-21
.....................\............\.........\demofun.m,3864,2003-02-21
.....................\............\.........\demomodel.m,4748,2005-09-13
.....................\............\.........\demo_fixedclass.m,2259,2003-03-11
.....................\............\.........\demo_fixedsize.m,3099,2003-02-21
.....................\............\.........\demo_yinyang.m,3337,2003-02-21
.....................\............\.........\denoise_kpca.m,3507,2003-02-21
.....................\............\.........\eign.m,3414,2003-02-21
.....................\............\.........\gridsearch.m,6927,2003-02-21
.....................\............\.........\initlssvm.m,4042,2003-02-21
.....................\............\.........\kentropy.m,2206,2003-02-21
.....................\............\.........\kernel_matrix.m,2182,2003-02-21
.....................\............\.........\kpca.m,4833,2003-02-21
.....................\............\.........\latentlssvm.m,2398,2003-02-21
.....................\............\.........\leaveoneout.m,5510,2003-02-21
.....................\............\.........\leaveoneout_lssvm.m,5215,2003-02-21
.....................\............\.........\linesearch.m,3758,2003-02-21
.....................\............\.........\linf.m,313,2003-02-21
.....................\............\.........\lin_kernel.m,516,2003-02-21
.....................\............\.........\LS-SVMlab Toolbox User's Guide.pdf,849975,2003-03-10
.....................\............\.........\lssvm.dll,22528,2003-02-21
.....................\............\.........\lssvm1024.dll,22528,2003-02-21
.....................\............\.........\lssvm256.dll,22528,2003-02-21

下载说明：请别用迅雷下载，失败请重下，重下不扣分！

发表评论

0 个回复

  • laplacian_enhancement
    lapla图像增强，可用于图像的增强处理，以有利于后期的特征提取等应用(lapla image enhancement, can be used for image enhancement in order to facilitate the later feature extraction applications)
    2010-11-21 13:43:53下载
    积分：1
  • ISA_book_example
    Matlab Coce for PCA 3
    2012-05-08 21:06:14下载
    积分：1
  • puma3dfiles
    The modeling and attitude stabilization control problems of a four-rotor vertical takeoff and landing unmanned air vehicle (UAV) known as the quadrotor are investigated.The quadrotor’s attitude is represented by the unit quaternion rather than Euler angles to avoid singularity problem. Taking dynamical behavior of motors into consideration and ignoring aerodynamic effect, a nonlinear controller is developed to stabilize the attitude.The control design is accomplished by using backstepping control technique.The proposed control law is based on the compensation for the Coriolis and gyroscope torques. Applying Lyapunov stability analysis proves that the closed-loop attitude system is asymptotic stable. Moreover, the controller can guarantee that all the states of the system are uniformly ultimately bounded in the presence of external disturbance torque.The effectiveness of the proposed control approach is analytically authenticated and also validated via simulation study.
    2014-09-04 19:00:04下载
    积分：1
  • rrsqrt2
    This is more efficient than RRSQRT
    2012-08-10 00:31:13下载
    积分：1
  • DocumentHandler
    Receive notification of general document events.
    2014-01-17 12:04:11下载
    积分：1
  • JADE
    一种差分进化算法的变体，收敛性能及其优秀，大家可以参考(a variant based on differential evolution algorithm,which has a better convergence performance.)
    2020-12-04 09:29:24下载
    积分：1
  • zuoye
    这是一个我们平时的作业，里面的内容是关于MATLAB的，希望大家觉得有用(This is one of our normal operations, which the content is on the MATLAB, and hope you find it useful)
    2011-05-14 17:33:00下载
    积分：1
  • matlabchuxue
    matalab一些基本运算，对于初学者来说很有用！(matalab some of the basic operations for the newcomer useful!)
    2007-04-17 08:53:04下载
    积分：1
  • image
    program to get an image in matlab
    2014-09-24 12:07:57下载
    积分：1
  • 建模文献
    分析橡胶挤出到人工分剪过程中的运动，以适应企业所生产所有规格橡胶为目标；以台达SV2型号PLC为控制核心，采用惠斯通电桥压电式传感器实时采集橡胶重量变化；针对现场加工环境中产生的振动干扰，并分析称重传感器采集到的称重信号；针对分剪系统响应速度与橡胶挤出速度匹配问题导致的不同挤出速度下误差的分布不同，且随着挤出速度的增大导致所分剪橡胶误差也增大的问题，(The movement of rubber extrusion to artificial shearing process is analyzed in order to adapt to the rubber of all specifications produced by the enterprise. Taking the delta SV2 model PLC as the control core and using the Wheatstone bridge piezoelectric sensor to collect the change of rubber weight in real time, the vibration interference produced in the field processing environment and the analysis of the weighing sensor are analyzed. The set of weighing signals; the distribution of errors at different extrusion speeds caused by the matching of the response speed of the shear system to the rubber extrusion speed is different, and the error of the shear rubber increases with the increase of the extrusion speed.)
    2018-04-19 21:49:52下载
    积分：1
  • 696516资源总数
  • 106914会员总数
  • 0今日下载

热门标签

Visual C++ matlab C/C++ Java Others Unix_Linux EasyLanguage易语言 Visual Basic C# PDF C++ Delphi VHDL ASP WINDOWS
热门下载

Copyright© 2019-2026 | Powered by Imdn | 浙ICP备16007336号 | IMDN交流 | 联系客服（QQ：3324461878）

本网站资源收集自网络及网站用户上传，若有侵权请邮件至（3324461878@qq.com），核实后我们会在24小时内删除，谢谢！