gusucode.com > 支持向量机工具箱 - LIBSVM OSU_SVM LS_SVM源码程序 > 支持向量机工具箱 - LIBSVM OSU_SVM LS_SVM\OSU_SVM3.00\demo\c_clademo.m
echo off % CLADEMO demonstration for using a contructed SVM classifier to classify % input patterns echo on; % % % NOTICE: please first run any of the first three demonstrations before % running this, because this demonstrate needs the results obtained % from any of the previous demonstrations. % pause clc % CLADEMO demonstration for using a contructed SVM classifier to classify % input patterns %########################################################################## % % This is a demonstration script-file for classifying the % input patterns using a constructed SVM classifier % %########################################################################## pause % Strike any key to continue (Note: use Ctrl-C to abort) clc %########################################################################## % % Classify input patterns using the constructed SVM Classifier % %########################################################################## pause % Strike any key to continue % Load the constructed SVM classifier clear all load SVMClassifier pause % Strike any key to continue % have a look at the variables determining the SVM classifier who pause % Strike any key to continue % load the patterns load DemoData_class pause % Strike any key to continue % Classify input patterns using the constructed nonlinear SVM Classifier % begin classification ...... [Labels, DecisionValue]= SVMClass(Samples, AlphaY, SVs, Bias, Parameters, nSV, nLabel); % end of the classification pause % Strike any key to continue % Compare the resultant labels with the true labels of the data plot(1:length(TrueLabels),TrueLabels,'b-',1:length(TrueLabels),Labels,'r.'); ylabel('Class Index'); xlabel('Pattern Index'); legend('True Labels','Resultant Labels',0); pause % Strike any key to continue echo off