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MATALB中SVM工具箱快速入手简易教程（常出现的错误解决办法）——胡matlab 自带的函数(matlab帮助文件里的例子)[只有较新版本的matlab中有这两个SVM的函数]（本人使用的是2012版本）svmtrain svmclassify=====简要语法规则====svmtrainTrain support vector machine classifierSyntaxSVMStruct = svmtrain(Training, Group)SVMStruct = svmtrain(..., 'Kernel_Function', Kernel_FunctionValue, ...) SVMStruct = svmtrain(..., 'RBF_Sigma', RBFSigmaValue, ...)SVMStruct = svmtrain(..., 'Polyorder', PolyorderValue, ...) SVMStruct = svmtrain(..., 'Mlp_Params', Mlp_ParamsValue, ...) SVMStruct = svmtrain(..., 'Method', MethodValue, ...)SVMStruct = svmtrain(..., 'QuadProg_Opts', QuadProg_OptsValue, ...) SVMStruct = svmtrain(..., 'SMO_Opts', SMO_OptsValue, ...)SVMStruct = svmtrain(..., 'BoxConstraint', BoxConstraintValue, ...) SVMStruct = svmtrain(..., 'Autoscale', AutoscaleValue, ...) SVMStruct = svmtrain(..., 'Showplot', ShowplotValue, ...)---------------------svmclassifyClassify data using support vector machineSyntaxGroup = svmclassify(SVMStruct, Sample)Group = svmclassify(SVMStruct, Sample, 'Showplot', ShowplotValue)实例操作：在命令行中输入一下内容：（或者新建一个脚本文件）警告：如果你之前安装过libsvm工具箱，则一下程序是不能执行的，并且会出现错误（如下图）。
最小二乘支持向量机1.6版前言对于以前的版本1.5版的工具箱和更新现有的一些命令我们增加了新功能。
由于许多读者都是熟悉的版本1.5布局，我们试图尽可能少地改变它。
主要的区别加速了一些方法的实现。
这里是一个简要的主要变化：Chapter/solver/function What’s newWhat’s new2. LS-SVMLab toolbox examples LS - SVM的路线图;增添更多的回归和分类的例子;界面更容易，多级分类; 改变执行了健全ls-svm。
3. Matlab functions 回归或分类的可能性只使用一条命令即可，功能验证已经被删除，更快（强劲）训练和（强大）模型选择标准被提供给用户，以防万一，稳健回归不同的函数必须要和与迭代重加权LS – SVM一起使用。
4. LS-SVM solver 所有CMEX和/或C文件已被删除。
求解线该性系统通过使用MATLAB命令“反斜杠”（\）第一章 引言在解决非线性分类，函数估计和密度估计问题中，支持向量机是一个很强大的方法，支持向量机也致使了其核心的新动向，最新发展事基于一般学习方法的。
支持向量机应经被引入统计学习理论和结构风险最小化之中。
这些方法中，凸优化问题,解决了一个典型的二次规划问题。
LS-SVM是标准SVM的改进，这样就可以解决线性kkt系统的问题了。
最小二乘支持向量机与正规化网络和高斯过程密切相关，但更加重视和利用原始对偶的规范条款解释。
经典的模式识别算法的内核版本如判别分析的内核Fisher，以非监督学习、循环式网络扩展和控制之间的链接是可用的。
健全性、稀疏性、权重可以被应用到LS-SVM上，并具有三个层次的推理贝叶斯框架已经制定。
LS – SVM像原始对偶那样配方给予核PCA，核CCA和PLS。
对于非常大的规模问题和在线学习，一个固定大小的LS - SVM方法被提出，它基于Nystrom在原始空间中支持向量的积极选择和估计的近似值。
我是在matlab环境中运行的，matlab安装在d盘，采用lssvm工具箱，lssvm工具箱安装在toolbox中，工具箱路径已经设置过，程序如下：clcclearclose all%---------------------------------------------------% 产生训练样本与测试样本n1 = 1:2:200;x1 = sin(n1*0.1);n2 = 2:2:200;x2 = sin(n2*0.1);xn_train = n1; % 训练样本，每一列为一个样本dn_train = x1; % 训练目标，行向量xn_test = n2; % 测试样本，每一列为一个样本dn_test = x2; % 测试目标，行向量%---------------------------------------------------% 参数设置X = xn_train';Y = dn_train';Xt = xn_test';Yt = dn_test';type = 'f';kernel = 'RBF_kernel';gam = 100; % Regularization parametersig2 = 0.01; % Kernel parameter (bandwidth in the case of the 'RBF_kernel'model = initlssvm(X,Y,type,gam,sig2,kernel); % 模型初始化%---------------------------------------------------% 交叉验证优化参数costfun = 'rcrossvalidate';costfun_args = {X,Y,10};optfun = 'gridsearch';model = tunelssvm(model,[],optfun,{},costfun,costfun_args); % 模型参数优化%---------------------------------------------------% 训练与测试model = trainlssvm(model); % 训练Yd = simlssvm(model,Xt); % 回归%---------------------------------------------------% 结果作图plot(1:length(Yt),Yt,'r+:',1:length(Yd),Yd,'bo:')title('+为真实值，o为预测值')但是我运行以后，出现以下错误：??? No appropriate methods for function range.Error in ==> D:\MATLAB6p5p1\toolbox\ls_svmlab\gridsearch.mOn line 163 ==> zoom = range(gridF(:,1))*range(gridF(:,2));Error in ==> D:\MATLAB6p5p1\toolbox\ls_svmlab\tunelssvm.mOn line 209 ==> [gs, cost, evals, fig] = feval(optfun,@costofmodel2,start values,{model, costfun,costargs},optargs{:});Error in ==> D:\MATLAB6p5p1\work\galssvm\lssvm\Regression_LS_SVMlab.mOn line 50 ==> model = tunelssvm(model,[],optfun,{},costfun,costfun_args);% 模型参数优化我的问题是1.程序为什么会出错？2.程序中如果采用4折交叉验证，是否应该将model = tunelssvm(model,[], optfun,{},costfun,costfun_args)中的costfun_args赋值为costfun_args＝{X,Y,4}。
1.文件中数据格式label index1:value1 index2:value2 ...Label在分类中表示类别标识，在预测中表示对应的目标值Index表示特征的序号，一般从1开始，依次增大Value表示每个特征的值例如：3 1:0.122000 2:0.7920003 1:0.144000 2:0.7500003 1:0.194000 2:0.6580003 1:0.244000 2:0.5400003 1:0.328000 2:0.4040003 1:0.402000 2:0.3560003 1:0.490000 2:0.3840003 1:0.548000 2:0.436000数据文件准备好后，可以用一个python程序检查格式是否正确，这个程序在下载的libsvm文件夹的子文件夹tools下，叫checkdata.py,用法：在windows命令行中先移动到checkdata.py 所在文件夹下，输入：checkdata.py 你要检查的文件完整路径（包含文件名）回车后会提示是否正确。
2.对数据进行归一化。
该过程要用到libsvm软件包中的svm-scale.exeSvm-scale用法：用法：svmscale [-l lower] [-u upper] [-y y_lowery_upper] [-s save_filename] [-r restore_filename] filename （缺省值： lower = -1，upper = 1，没有对y进行缩放）其中， -l：数据下限标记；lower：缩放后数据下限；-u：数据上限标记；upper：缩放后数据上限；-y：是否对目标值同时进行缩放；y_lower为下限值，y_upper为上限值；（回归需要对目标进行缩放，因此该参数可以设定为 –y -1 1 ）-s save_filename：表示将缩放的规则保存为文件save_filename；-r restore_filename：表示将缩放规则文件restore_filename载入后按此缩放；filename：待缩放的数据文件（要求满足前面所述的格式）。
1.1 如果是Matlab安装光盘上的工具箱，重新执行安装程序，选中即可；1.2 如果是单独下载的工具箱，一般情况下仅需要把新的工具箱解压到某个目录。
2 在matlab的file下面的set path把它加上。
3 把路径加进去后在file→Preferences→General的Toolbox Path Caching里点击update Toolbox Path Cache更新一下。
4 用which newtoolbox_command.m来检验是否可以访问。
如果能够显示新设置的路径，则表明该工具箱可以使用了。
把你的工具箱文件夹放到安装目录中“toolbox”文件夹中，然后单击“file”菜单中的“setpath”命令，打开“setpath”对话框，单击左边的“ADDFolder”命令，然后选择你的那个文件夹，最后单击“SAVE”命令就OK了。
MATLAB Toolboxes＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝/zsmcode.htmlBinaural-modeling software for MATLAB/Windows/home/Michael_Akeroyd/download2.htmlStatistical Parametric Mapping (SPM)/spm/ext/BOOTSTRAP MATLAB TOOLBOX.au/downloads/bootstrap_toolbox.htmlThe DSS package for MATLABDSS Matlab package contains algorithms for performing linear, deflation and symmetric DSS. http://www.cis.hut.fi/projects/dss/package/Psychtoolbox/download.htmlMultisurface Method Tree with MATLAB/~olvi/uwmp/msmt.htmlA Matlab Toolbox for every single topic !/~baum/toolboxes.htmleg. BrainStorm - MEG and EEG data visualization and processingCLAWPACK is a software package designed to compute numerical solutions to hyperbolic partial differential equations using a wave propagation approach/~claw/DIPimage - Image Processing ToolboxPRTools - Pattern Recognition Toolbox (+ Neural Networks)NetLab - Neural Network ToolboxFSTB - Fuzzy Systems ToolboxFusetool - Image Fusion Toolboxhttp://www.metapix.de/toolbox.htmWAVEKIT - Wavelet ToolboxGat - Genetic Algorithm ToolboxTSTOOL is a MATLAB software package for nonlinear time series analysis.TSTOOL can be used for computing: Time-delay reconstruction, Lyapunov exponents, Fractal dimensions, Mutual information, Surrogate data tests, Nearest neighbor statistics, Return times, Poincare sections, Nonlinear predictionhttp://www.physik3.gwdg.de/tstool/MATLAB / Data description toolboxA Matlab toolbox for data description, outlier and novelty detectionMarch 26, 2004 - D.M.J. Taxhttp://www-ict.ewi.tudelft.nl/~davidt/dd_tools/dd_manual.htmlMBEhttp://www.pmarneffei.hku.hk/mbetoolbox/Betabolic network toolbox for Matlabhttp://www.molgen.mpg.de/~lieberme/pages/network_matlab.htmlPharmacokinetics toolbox for Matlabhttp://page.inf.fu-berlin.de/~lieber/seiten/pbpk_toolbox.htmlThe SpiderThe spider is intended to be a complete object orientated environment for machine learning in Matlab. Aside from easy use of base learning algorithms, algorithms can be plugged together and can be compared with, e.g model selection, statistical tests and visual plots. This gives all the power of objects (reusability, plug together, share code) but also all the power of Matlab for machine learning research.http://www.kyb.tuebingen.mpg.de/bs/people/spider/index.htmlSchwarz-Christoffel Toolbox/matlabcentral/fileexchange/loadFile.do?objectId=1316&objectT ype=file#XML Toolbox/matlabcentral/fileexchange/loadFile.do?objectId=4278&object Type=fileFIR/TDNN Toolbox for MATLABBeta version of a toolbox for FIR (Finite Impulse Response) and TD (Time Delay) NeuralNetworks./interval-comp/dagstuhl.03/oish.pdfMisc.http://www.dcsc.tudelft.nl/Research/Software/index.htmlAstronomySaturn and Titan trajectories ... MALTAB astronomy/~abrecht/Matlab-codes/AudioMA Toolbox for Matlab Implementing Similarity Measures for Audiohttp://www.oefai.at/~elias/ma/index.htmlMAD - Matlab Auditory Demonstrations/~martin/MAD/docs/mad.htmMusic Analysis - Toolbox for Matlab : Feature Extraction from Raw Audio Signals for Content-Based Music Retrihttp://www.ai.univie.ac.at/~elias/ma/WarpTB - Matlab Toolbox for Warped DSPBy Aki Härmä and Matti Karjalainenhttp://www.acoustics.hut.fi/software/warp/MATLAB-related Softwarehttp://www.dpmi.tu-graz.ac.at/~schloegl/matlab/Biomedical Signal data formats (EEG machine specific file formats with Matlab import routines)http://www.dpmi.tu-graz.ac.at/~schloegl/matlab/eeg/MPEG Encoding library for MATLAB Movies (Created by David Foti)It enables MATLAB users to read (MPGREAD) or write (MPGWRITE) MPEG movies. That should help Video Quality project.Filter Design packagehttp://www.ee.ryerson.ca:8080/~mzeytin/dfp/index.htmlOctave by Christophe COUVREUR (Generates normalized A-weigthing, C-weighting, octave and one-third-octave digital filters)/matlabcentral/fileexchange/loadFile.do?objectType=file&object Id=69Source Coding MATLAB Toolbox/users/kieffer/programs.htmlBio Medical Informatics (Top)CGH-Plotter: MATLAB Toolbox for CGH-data AnalysisCode: http://sigwww.cs.tut.fi/TICSP/CGH-Plotter/Poster: http://sigwww.cs.tut.fi/TICSP/CSB2003/Posteri_CGH_Plotter.pdfThe Brain Imaging Software Toolboxhttp://www.bic.mni.mcgill.ca/software/MRI Brain Segmentation/matlabcentral/fileexchange/loadFile.do?objectId=4879Chemometrics (providing PCA) (Top)Matlab Molecular Biology & Evolution Toolbox(Toolbox Enables Evolutionary Biologists to Analyze and View DNA and Protein Sequences) James J. Caihttp://www.pmarneffei.hku.hk/mbetoolbox/Toolbox provided by Prof. Massart research grouphttp://minf.vub.ac.be/~fabi/publiek/Useful collection of routines from Prof age smilde research grouphttp://www-its.chem.uva.nl/research/pacMultivariate Toolbox written by Rune Mathisen/~mvartools/index.htmlMatlab code and datasetshttp://www.acc.umu.se/~tnkjtg/chemometrics/dataset.htmlChaos (Top)Chaotic Systems Toolbox/matlabcentral/fileexchange/loadFile.do?objectId=1597&objectT ype=file#HOSA Toolboxhttp://www.mathworks.nl/matlabcentral/fileexchange/loadFile.do?objectId=3013&objectTy pe=fileChemistry (Top)MetMAP - (Metabolical Modeling, Analysis and oPtimization alias Met. M. A. P.)http://webpages.ull.es/users/sympbst/pag_ing/pag_metmap/index.htmDoseLab - A set of software programs for quantitative comparison of measured and computed radiation dose distributions/GenBank Overview/Genbank/GenbankOverview.htmlMatlab: /matlabcentral/fileexchange/loadFile.do?objectId=1139CodingCode for the estimation of Scaling Exponentshttp://www.cubinlab.ee.mu.oz.au/~darryl/secondorder_code.htmlControl (Top)Control Tutorial for Matlab/group/ctm/AnotherCommunications (Top)Channel Learning Architecture toolbox(This Matlab toolbox is a supplement to the article "HiperLearn: A High Performance Learning Architecture")http://www.isy.liu.se/cvl/Projects/hiperlearn/Source Coding MATLAB Toolbox/users/kieffer/programs.htmlTCP/UDP/IP Toolbox 2.0.4/matlabcentral/fileexchange/loadFile.do?objectId=345&objectT ype=fileHome Networking Basis: Transmission Environments and Wired/Wireless Protocols Walter Y. Chen/support/books/book5295.jsp?category=new&language=-1MATLAB M-files and Simulink models/matlabcentral/fileexchange/loadFile.do?objectId=3834&object Type=file•OPNML/MATLAB Facilities/OPNML_Matlab/Mesh Generation/home/vavasis/qmg-home.htmlOpenFEM : An Open-Source Finite Element Toolbox/CALFEM is an interactive computer program for teaching the finite element method (FEM)http://www.byggmek.lth.se/Calfem/frinfo.htmThe Engineering Vibration Toolbox/people/faculty/jslater/vtoolbox/vtoolbox.htmlSaGA - Spatial and Geometric Analysis Toolboxby Kirill K. Pankratov/~glenn/kirill/saga.htmlMexCDF and NetCDF Toolbox For Matlab-5&6/staffpages/cdenham/public_html/MexCDF/nc4ml5.htmlCUEDSID: Cambridge University System Identification Toolbox/jmm/cuedsid/Kriging Toolbox/software/Geostats_software/MATLAB_KRIGING_TOOLBOX.htmMonte Carlo (Dr Nando)http://www.cs.ubc.ca/~nando/software.htmlRIOTS - The Most Powerful Optimal Control Problem Solver/~adam/RIOTS/ExcelMATLAB xlsheets/matlabcentral/fileexchange/loadFile.do?objectId=4474&objectTy pe=filewrite2excel/matlabcentral/fileexchange/loadFile.do?objectId=4414&objectTy pe=fileFinite Element Modeling (FEM) (Top)OpenFEM - An Open-Source Finite Element Toolbox/NLFET - nonlinear finite element toolbox for MATLAB ( framework for setting up, solving, and interpreting results for nonlinear static and dynamic finite element analysis.)/GetFEM - C++ library for finite element methods elementary computations with a Matlabinterfacehttp://www.gmm.insa-tlse.fr/getfem/FELIPE - FEA package to view results ( contains neat interface to MATLA/~blstmbr/felipe/Finance (Top)A NEW MATLAB-BASED TOOLBOX FOR COMPUTER AIDED DYNAMIC TECHNICAL TRADINGStephanos Papadamou and George StephanidesDepartment of Applied Informatics, University Of Macedonia Economic & Social Sciences, Thessaloniki, Greece/fen31/one_time_articles/dynamic_tech_trade_matlab6.htm Paper: :8089/eps/prog/papers/0201/0201001.pdfCompEcon Toolbox for Matlab/~pfackler/compecon/toolbox.htmlGenetic Algorithms (Top)The Genetic Algorithm Optimization Toolbox (GAOT) for Matlab 5/mirage/GAToolBox/gaot/Genetic Algorithm ToolboxWritten & distributed by Andy Chipperfield (Sheffield University, UK)/uni/projects/gaipp/gatbx.htmlManual: /~gaipp/ga-toolbox/manual.pdfGenetic and Evolutionary Algorithm Toolbox (GEATbx)/Evolutionary Algorithms for MATLAB/links/ea_matlab.htmlGenetic/Evolutionary Algorithms for MATLABhttp://www.systemtechnik.tu-ilmenau.de/~pohlheim/EA_Matlab/ea_matlab.html GraphicsVideoToolbox (C routines for visual psychophysics on Macs by Denis Pelli)/VideoToolbox/Paper: /pelli/pubs/pelli1997videotoolbox.pdf4D toolbox/~daniel/links/matlab/4DToolbox.htmlImages (Top)Eyelink Toolbox/eyelinktoolbox/Paper: /eyelinktoolbox/EyelinkToolbox.pdfCellStats: Automated statistical analysis of color-stained cell images in Matlabhttp://sigwww.cs.tut.fi/TICSP/CellStats/SDC Morphology Toolbox for MATLAB (powerful collection of latest state-of-the-art gray-scale morphological tools that can be applied to image segmentation, non-linear filtering, pattern recognition and image analysis)/Image Acquisition Toolbox/products/imaq/Halftoning Toolbox for MATLAB/~bevans/projects/halftoning/toolbox/index.htmlDIPimage - A Scientific Image Processing Toolbox for MATLABhttp://www.ph.tn.tudelft.nl/DIPlib/dipimage_1.htmlPNM Toolboxhttp://home.online.no/~pjacklam/matlab/software/pnm/index.htmlAnotherICA / KICA and KPCA (Top)ICA TU Toolboxhttp://mole.imm.dtu.dk/toolbox/menu.htmlMISEP Linear and Nonlinear ICA Toolboxhttp://neural.inesc-id.pt/~lba/ica/mitoolbox.htmlKernel Independant Component Analysis/~fbach/kernel-ica/index.htmMatlab: kernel-ica version 1.2KPCA- Please check the software section of kernel machines.KernelStatistical Pattern Recognition Toolboxhttp://cmp.felk.cvut.cz/~xfrancv/stprtool/MATLABArsenal A MATLAB Wrapper for Classification/tmp/MATLABArsenal.htmMarkov (Top)MapHMMBOX 1.1 - Matlab toolbox for Hidden Markov Modelling using Max. Aposteriori EM Prerequisites: Matlab 5.0, Netlab. Last Updated: 18 March 2002./~parg/software/maphmmbox_1_1.tarHMMBOX 4.1 - Matlab toolbox for Hidden Markov Modelling using Variational Bayes Prerequisites: Matlab 5.0,Netlab. Last Updated: 15 February 2002../~parg/software/hmmbox_3_2.tar/~parg/software/hmmbox_4_1.tarMarkov Decision Process (MDP) Toolbox for MatlabKevin Murphy, 1999/~murphyk/Software/MDP/MDP.zipMarkov Decision Process (MDP) Toolbox v1.0 for MATLABhttp://www.inra.fr/bia/T/MDPtoolbox/Hidden Markov Model (HMM) Toolbox for Matlab/~murphyk/Software/HMM/hmm.htmlBayes Net Toolbox for Matlab/~murphyk/Software/BNT/bnt.htmlMedical (Top)EEGLAB Open Source Matlab Toolbox for Physiological Research (formerly ICA/EEG Matlabtoolbox)/~scott/ica.htmlMATLAB Biomedical Signal Processing Toolbox/Toolbox/Powerful package for neurophysiological data analysis ( Igor Kagan webpage)/Matlab/Unitret.htmlEEG / MRI Matlab Toolbox/Microarray data analysis toolbox (MDAT): for normalization, adjustment and analysis of gene expression_r data.Knowlton N, Dozmorov IM, Centola M. Department of Arthritis and Immunology, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA 73104. We introduce a novel Matlab toolbox for microarray data analysis. This toolbox uses normalization based upon a normally distributed background and differential gene expression_r based on 5 statistical measures. The objects in this toolbox are open source and can be implemented to suit your application. AVAILABILITY: MDAT v1.0 is a Matlab toolbox and requires Matlab to run. MDAT is freely available at:/publications/2004/knowlton/MDAT.zipMIDI (Top)MIDI Toolbox version 1.0 (GNU General Public License)http://www.jyu.fi/musica/miditoolbox/Misc. (Top)MATLAB-The Graphing Tool/~abrecht/matlab.html3-D Circuits The Circuit Animation Toolbox for MATLAB/other/3Dcircuits/SendMailhttp://carol.wins.uva.nl/~portegie/matlab/sendmail/Coolplothttp://www.reimeika.ca/marco/matlab/coolplots.htmlMPI (Matlab Parallel Interface)Cornell Multitask Toolbox for MATLAB/Services/Software/CMTM/Beolab Toolbox for v6.5Thomas Abrahamsson (Professor, Chalmers University of Technology, Applied Mechanics,Göteborg, Sweden)http://www.mathworks.nl/matlabcentral/fileexchange/loadFile.do?objectId=1216&objectType =filePARMATLABNeural Networks (Top)SOM Toolboxhttp://www.cis.hut.fi/projects/somtoolbox/Bayes Net Toolbox for Matlab/~murphyk/Software/BNT/bnt.htmlNetLab/netlab/Random Neural Networks/~ahossam/rnnsimv2/ftp: ftp:///pub/contrib/v5/nnet/rnnsimv2/NNSYSID Toolbox (tools for neural network based identification of nonlinear dynamic systems) http://www.iau.dtu.dk/research/control/nnsysid.htmlOceanography (Top)WAFO. Wave Analysis for Fatigue and Oceanographyhttp://www.maths.lth.se/matstat/wafo/ADCP toolbox for MATLAB (USGS, USA)Presented at the Hydroacoustics Workshop in Tampa and at ADCP's in Action in San Diego /operations/stg/pubs/ADCPtoolsSEA-MAT - Matlab Tools for Oceanographic AnalysisA collaborative effort to organize and distribute Matlab tools for the Oceanographic Community /Ocean Toolboxhttp://www.mar.dfo-mpo.gc.ca/science/ocean/epsonde/programming.htmlEUGENE D. GALLAGHER(Associate Professor, Environmental, Coastal & Ocean Sciences)/edgwebp.htmOptimization (Top)MODCONS - a MATLAB Toolbox for Multi-Objective Control System Design/mecheng/jfw/modcons.htmlLazy Learning Packagehttp://iridia.ulb.ac.be/~lazy/SDPT3 version 3.02 -- a MATLAB software for semidefinite-quadratic-linear programming .sg/~mattohkc/sdpt3.htmlMinimum Enclosing Balls: Matlab Code/meb/SOSTOOLS Sum of Squares Optimi zation Toolbox for MATLAB User’s guide/sostools/sostools.pdfPSOt - a Particle Swarm Optimization Toolbox for use with MatlabBy Brian Birge ... A Particle Swarm Optimization Toolbox (PSOt) for use with the Matlab scientific programming environment has been developed. PSO isintroduced briefly and then the use of the toolbox is explained with some examples. A link to downloadable code is provided.Plot/software/plotting/gbplot/Signal Processing (Top)Filter Design with Motorola DSP56Khttp://www.ee.ryerson.ca:8080/~mzeytin/dfp/index.htmlChange Detection and Adaptive Filtering Toolboxhttp://www.sigmoid.se/Signal Processing Toolbox/products/signal/ICA TU Toolboxhttp://mole.imm.dtu.dk/toolbox/menu.htmlTime-Frequency Toolbox for Matlabhttp://crttsn.univ-nantes.fr/~auger/tftb.htmlVoiceBox - Speech Processing Toolbox/hp/staff/dmb/voicebox/voicebox.htmlLeast Squared - Support Vector Machines (LS-SVM)http://www.esat.kuleuven.ac.be/sista/lssvmlab/WaveLab802 : the Wavelet ToolboxBy David Donoho, Mark Reynold Duncan, Xiaoming Huo, Ofer Levi /~wavelab/Time-series Matlab scriptshttp://wise-obs.tau.ac.il/~eran/MATLAB/TimeseriesCon.htmlUvi_Wave Wavelet Toolbox Home Pagehttp://www.gts.tsc.uvigo.es/~wavelets/index.htmlAnotherSupport Vector Machine (Top)MATLAB Support Vector Machine ToolboxDr Gavin CawleySchool of Information Systems, University of East Anglia/~gcc/svm/toolbox/LS-SVM - SISTASVM toolboxes/dmi/svm/LSVM Lagrangian Support Vector Machine/dmi/lsvm/Statistics (Top)Logistic regression/SAGA/software/saga/Multi-Parametric Toolbox (MPT) A tool (not only) for multi-parametric optimization. http://control.ee.ethz.ch/~mpt/ARfit: A Matlab package for the estimation of parameters and eigenmodes of multivariate autoregressive modelshttp://www.mat.univie.ac.at/~neum/software/arfit/The Dimensional Analysis Toolbox for MATLABHome: http://www.sbrs.de/Paper: http://www.isd.uni-stuttgart.de/~brueckner/Papers/similarity2002.pdfFATHOM for Matlab/personal/djones/PLS-toolbox/Multivariate analysis toolbox (N-way Toolbox - paper)http://www.models.kvl.dk/source/nwaytoolbox/index.aspClassification Toolbox for Matlabhttp://tiger.technion.ac.il/~eladyt/classification/index.htmMatlab toolbox for Robust Calibrationhttp://www.wis.kuleuven.ac.be/stat/robust/toolbox.htmlStatistical Parametric Mapping/spm/spm2.htmlEVIM: A Software Package for Extreme Value Analysis in Matlabby Ramazan Gençay, Faruk Selcuk and Abdurrahman Ulugulyagci, 2001.Manual (pdf file) evim.pdf - Software (zip file) evim.zipTime Series Analysishttp://www.dpmi.tu-graz.ac.at/~schloegl/matlab/tsa/Bayes Net Toolbox for MatlabWritten by Kevin Murphy/~murphyk/Software/BNT/bnt.htmlOther: /information/toolboxes.htmlARfit: A Matlab package for the estimation of parameters and eigenmodes of multivariate autoregressive models/~tapio/arfit/M-Fithttp://www.ill.fr/tas/matlab/doc/mfit4/mfit.htmlDimensional Analysis Toolbox for Matlab/The NaN-toolbox: A statistic-toolbox for Octave and Matlab®... handles data with and without MISSING VALUES.http://www-dpmi.tu-graz.ac.at/~schloegl/matlab/NaN/Iterative Methods for Optimization: Matlab Codes/~ctk/matlab_darts.htmlMultiscale Shape Analysis (MSA) Matlab Toolbox 2000p.br/~cesar/projects/multiscale/Multivariate Ecological & Oceanographic Data Analysis (FATHOM)From David Jones/personal/djones/glmlab (Generalized Linear Models in MATLA.au/staff/dunn/glmlab/glmlab.htmlSpacial and Geometric Analysis (SaGA) toolboxInteresting audio links with FAQ, VC++, on the topic机器学习网站北京大学视觉与听觉信息处理实验室北京邮电大学模式识别与智能系统学科复旦大学智能信息处理开放实验室IEEE Computer Society北京映象站点计算机科学论坛机器人足球赛模式识别国家重点实验室南京航空航天大学模式识别与神经计算实验室- PARNEC南京大学机器学习与数据挖掘研究所- LAMDA南京大学人工智能实验室南京大学软件新技术国家重点实验室人工生命之园数据挖掘研究院微软亚洲研究院中国科技大学人工智能中心中科院计算所中科院计算所生物信息学实验室中科院软件所中科院自动化所中科院自动化所人工智能实验室ACL Special Interest Group on Natural Language Learning (SIGNLL)ACMACM Digital LibraryACM SIGARTACM SIGIRACM SIGKDDACM SIGMODAdaptive Computation Group at University of New MexicoAI at Johns HopkinsAI BibliographiesAI Topics: A dynamic online library of introductory information about artificial intelligence Ant Colony OptimizationARIES Laboratory: Advanced Research in Intelligent Educational SystemsArtificial Intelligence Research in Environmental Sciences (AIRIES)Austrian Research Institute for AI (OFAI)Back Issues of Neuron DigestBibFinder: a computer science bibliography search engine integrating many other engines BioAPI ConsortiumBiological and Computational Learning Center at MITBiometrics ConsortiumBoosting siteBrain-Style Information Systems Research Group at RIKEN Brain Science Institute, Japan British Computer Society Specialist Group on Expert SystemsCanadian Society for Computational Studies of Intelligence (CSCSI)CI Collection of BibTex DatabasesCITE, the first-stop source for computational intelligence information and services on the web Classification Society of North AmericaCMU Advanced Multimedia Processing GroupCMU Web->KB ProjectCognitive and Neural Systems Department of Boston UniversityCognitive Sciences Eprint Archive (CogPrints)COLT: Computational Learning TheoryComputational Neural Engineering Laboratory at the University of FloridaComputational Neurobiology Lab at California, USAComputer Science Department of National University of SingaporeData Mining Server Online held by Rudjer Boskovic InstituteDatabase Group at Simon Frazer University, CanadaDBLP: Computer Science BibliographyDigital Biology: about creating artificial lifeDistributed AI Unit at Queen Mary & Westfield College, University of LondonDistributed Artificial Intelligence at HUJIDSI Neural Networks group at the Université di Firenze, ItalyEA-related literature at the EvALife research group at DAIMI, University of Aarhus, Denmark Electronic Research Group at Aberdeen UniversityElsevierComputerScienceEuropean Coordinating Committee for Artificial Intelligence (ECCAI)European Network of Excellence in ML (MLnet)European Neural Network Society (ENNS)Evolutionary Computing Group at University of the West of EnglandEvolutionary Multi-Objective Optimization RepositoryExplanation-Based Learning at University of Illinoise at Urbana-ChampaignFace Detection HomepageFace Recognition Vendor TestFace Recognition HomepageFace Recognition Research CommunityFingerpassftp of Jude Shavlik's Machine Learning Group (University of Wisconsin-Madison)GA-List Searchable DatabaseGenetic Algorithms Digest ArchiveGenetic Programming BibliographyGesture Recognition HomepageHCI Bibliography Project contain extended bibliographic information (abstract, key words, table of contents, section headings) for most publications Human-Computer Interaction dating back to 1980 and selected publications before 1980IBM ResearchIEEEIEEE Computer SocietyIEEE Neural Networks SocietyIllinois Genetic Algorithms Laboratory (IlliGAL)ILP Network of ExcellenceInductive Learning at University of Illinoise at Urbana-ChampaignIntelligent Agents RepositoryIntellimedia Project at North Carolina State UniversityInteractive Artificial Intelligence ResourcesInternational Association of Pattern RecognitionInternational Biometric Industry AssociationInternational Joint Conference on Artificial Intelligence (IJCAI)International Machine Learning Society (IMLS)International Neural Network Society (INNS)Internet Softbot Research at University of WashingtonJapanese Neural Network Society (JNNS)Java Agents for Meta-Learning Group (JAM) at Computer Science Department, Columbia University, for Fraud and Intrusion Detection Using Meta-Learning AgentsKernel MachinesKnowledge Discovery MineLaboratory for Natural and Simulated Cognition at McGill University, CanadaLearning Laboratory at Carnegie Mellon UniversityLearning Robots Laboratory at Carnegie Mellon UniversityLaboratoire d'Informatique et d'Intelligence Artificielle (IIA-ENSAIS)Machine Learning Group of Sydney University, AustraliaMammographic Image Analysis SocietyMDL Research on the WebMirek's Cellebration: 1D and 2D Cellular Automata explorerMIT Artificial Intelligence LaboratoryMIT Media LaboratoryMIT Media Laboratory Vision and Modeling GroupMLNET: a European network of excellence in Machine Learning, Case-based Reasoning and Knowledge AcquisitionMLnet Machine Learning Archive at GMD includes papers, software, and data sets MIRALab at University of Geneva: leading research on virtual human simulationNeural Adaptive Control Technology (NACT)Neural Computing Research Group at Aston University, UKNeural Information Processing Group at Technical University of BerlinNIPSNIPS OnlineNeural Network Benchmarks, Technical Reports,and Source Code maintained by Scott Fahlman at CMU; source code includes Quickprop, Cascade-Correlation, Aspirin/Migraines Neural Networks FAQ by Lutz PrecheltNeural Networks FAQ by Warren S. SarleNeural Networks: Freeware and Shareware ToolsNeural Network Group at Department of Medical Physics and Biophysics, University ofNeural Network Group at Université Catholique de LouvainNeural Network Group at Eindhoven University of TechnologyNeural Network Hyperplane Animator program that allows easy visualization of training data and weights in a back-propagation neural networkNeural Networks Research at TUT/ELENeural Networks Research Centre at Helsinki University of Technology, FinlandNeural Network Speech Group at Carnegie Mellon UniversityNeural Text Classification with Neural NetworksNonlinearity and Complexity HomepageOFAI and IMKAI library information system, provided by the Department of Medical Cybernetics and Artificial Intelligence at the University of Vienna (IMKAI) and the Austrian Research Institute for Artificial Intelligence (OFAI). It contains over 36,000 items (books, research papers, conference papers, journal articles) from many subareas of AI OntoWeb: Ontology-based information exchange for knowledge management and electronic commercePortal on Neural Network ForecastingPRAG: Pattern Recognition and Application Group at University of CagliariQuest Project at IBM Almaden Research Center: an academic website focusing on classification and regression trees. Maintained by Tjen-Sien LimReinforcement Learning at Carnegie Mellon UniversityResearchIndex: NECI Scientific Literature Digital Library, indexing over 200,000 computer science articlesReVision: Reviewing Vision in the Web!RIKEN: The Institute of Physical and Chemical Research, JapanSalford SystemsSANS Studies of Artificial Neural Systems, at the Royal Institute of Technology, Sweden Santa-Fe InstituteScirus: a search engine locating scientific information on the InternetSecond Moment: The News and Business Resource for Applied AnalyticsSEL-HPC Article Archive has sections for neural networks, distributed AI, theorem proving, and a variety of other computer science topicsSOAR Project at University of Southern CaliforniaSociety for AI and StatisticsSVM of ANU CanberraSVM of Bell LabsSVM of GMD-First BerlinSVM of MITSVM of Royal Holloway CollegeSVM of University of SouthamptonSVM-workshop at NIPS97TechOnLine: TechOnLine University offers free online courses and lecturesUCI Machine Learning GroupUMASS Distributed Artificial Intelligence LaboratoryUTCS Neural Networks Research Group of Artificial Intelligence Lab, Computer Science Department, University of Texas at AustinVivisimo Document Clustering: a powerful search engine which returns clustered results Worcester Polytechnic Institute Artificial Intelligence Research Group (AIRG)Xerion neural network simulator developed and used by the connectionist group at the University of TorontoYale's CTAN Advanced Technology Center for Theoretical and Applied Neuroscience ZooLand: Artificial Life Resource。
四种支持向量机用于函数拟合与模式识别的Matlab示例程序陆振波点这里下载：四种支持向量机用于函数拟合与模式识别的Matlab示例程序使用要点：应研学论坛《人工智能与模式识别》版主magic_217之约，写一个关于针对初学者的《四种支持向量机工具箱》的详细使用说明。
同时也不断有网友向我反映看不懂我的源代码，以及询问如何将该工具箱应用到实际数据分析等问题，其中有相当一部分网友并不了解模式识别的基本概念，就急于使用这个工具箱。
本文从模式识别的基本概念谈起，过渡到神经网络模式识别，逐步引入到这四种支持向量机工具箱的使用。
本文适合没有模式识别基础，而又急于上手的初学者。
作者水平有限，欢迎同行批评指正！[1]模式识别基本概念模式识别的方法有很多，常用有：贝叶斯决策、神经网络、支持向量机等等。
特别说明的是，本文所谈及的模式识别是指“有师分类”，即事先知道训练样本所属的类别，然后设计分类器，再用该分类器对测试样本进行识别，比较测试样本的实际所属类别与分类器输出的类别，进而统计正确识别率。
正确识别率是反映分类器性能的主要指标。
分类器的设计虽然是模式识别重要一环，但是样本的特征提取才是模式识别最关键的环节。
试想如果特征矢量不能有效地描述原样本，那么即使分类设计得再好也无法实现正确分类。
工程中我们所遇到的样本一般是一维矢量，如：语音信号，或者是二维矩阵，如：图片等。
特征提取就是将一维矢量或二维矩阵转化成一个维数比较低的特征矢量，该特征矢量用于分类器的输入。
关于特征提取，在各专业领域中也是一个重要的研究方向，如语音信号的谐振峰特征提取，图片的PCA特征提取等等。
[2]神经网络模式识别神经网络模式识别的基本原理是，神经网络可以任意逼近一个多维输入输出函数。
以三类分类：I、II、III为例，神经网络输入是样本的特征矢量，三类样本的神经网络输出可以是[1;0;0]、[0;1;0]、[0;0;1]，也可以是[1;-1;-1]、[-1;1;-1]、[-1;-1;1]。
libsvm-mat-加强工具箱介绍由于libsvm的matlab版本的工具箱libsvm-mat并没有给出寻参的函数模块，而无论利用libsvm工具箱进行分类还是回归，参数的选取是十分重要的，鉴于此libsvm-mat-加强工具箱在libsvm-mat-2.89-3的基础上给出相应的辅助函数插件，方便用户来选取最佳的参数，该加强工具箱可以在MATLAB中文论坛上下载，现对该加强工具箱里主要的辅助函数插件的接口进行介绍，所有的源代码可以到MATLAB中文论坛下载并查看。
====================================================== ====归一化函数:scaleForSVM[train_scale,test_scale,ps]= scaleForSVM(train_data,test_data,ymin,ymax) 输入：train_data:训练集，格式要求与svmtrain相同。
test_data:测试集，格式要求与svmtrain相同。
ymin，ymax:归一化的范围，即将训练集和测试都归一化到[ymin,ymax]，这两个参数可不输入，默认值为ymin=0，ymax=1，即默认将训练集和测试都归一化到[0,1]。
输出：train_scale:归一化后的训练集。
test_scale:归一化后的测试集。
ps:归一化过程中的映射（方便反归一化使用）。
====================================================== ====pca降维预处理函数：pcaForSVM[train_pca,test_pca] = pcaForSVM(train_data,test_data,threshold)输入：train_data:训练集，格式要求与svmtrain相同。
test_data:测试集，格式要求与svmtrain相同。
/~piaip/svm/svm_tutorial.htmlSVM:什么是SVM，它能为我们做什么?SVM, Support Vector Machine, 简而言之它是个起源与人工神经网络有点像的东西，现今最常拿来就是做分类。
也就是说，如果我有一堆已经分好类的东西（可是分类的依据是未知的），那当收到新的东西时，SVM可以预测新的数据要分到哪一堆去。
听起来是很神奇的事（如果你觉得不神奇，请重想一想这句话代表什么：分类的依据是未知的！，还是不神奇的话就请你写个程序，解解上面的问题），不过SVM基于统计学习理论的，可以在合理的时间内漂亮的解决这个问题。
以图形化的例子来说明,假定我在空间中标了一堆用颜色分类的点, 点的颜色就是它的类别, 位置就是它的数据, 那SVM就可以找出区隔这些点的程序, 依此就可以分出一个个的区域; 拿到新的点(数据) 时, 只要对照该位置在哪一区就可以找出它应该是哪一颜色(类别)了。
当然SVM不是真的只有分区那么简单, 不过看上面的例子应该可以了解SVM大概在作什么. 要对SVM再多懂一点点，可以参考 cjlin 在 data mining 课的slides:pdf或ps。
我们可以把SVM当个黑盒子, 数据丢进去让他处理然后我们再来用就好了.哪里得到SVM?libsvm当然是最完美的工具.下载处: libsvm.zip或者libsvm.tar.gz.zip跟 .tar.gz 基本上是一样的, 只是看你的操作系统; 习惯上 Windows 用 .zip 比较方便(因为有WinZIP, 也有WinRAR), UNIX 则是用 .tar.gz编译libsvm解开来后, 假定是UNIX 系统, 直接打 make 就可以了; 编不出来的话请详读说明和运用常识. 因为这是指南, 所以我不花时间细谈, 而且编不出来的情形真是少之又少, 通常一定是你的系统有问题。
其他的子目录可以不管, 只要svm-train, svm-scale,svm-predict三个执行文件有就可以了. Windows 的用户要自己重编当然也是可以, 不过已经有编好的执行文件在里面了: 请检查 windows 子目录, 应该会有svmtrain.exe, svmscale.exe, svmpredict.exe, svmtoy.exe.SVM的使用libsvm 有很多种用法, 这篇指南只打算讲简单的部分.程序svmtrain训练数据. 跑SVM被戏称为“开火车” 也是由于这个程序名而来. train会接受特定格式的输入, 产生一个“Model” 文件. 这个 model 你可以想像成SVM的内部数据,因为预测要model才能预测, 不能直接吃原始数据.想想也很合理,假定 train 本身是很耗时的动作, 而 train可以以某种形式存起内部数据,那下次要预测时直接把那些内部数据载入就快多了.svmpredict依照已经训练好的 model, 再加上给定的输入(新值), 输出预测新值所对应的类别. svmscale扫描数据. 因为原始数据可能范围过大或过小, svmscale 可以先将数据重新 scale (缩放) 到适当范围使训练与预测速度更快。
