svm.rar_CRZ_SVM分类matlab

function svm() clc; clear all; close all; trainData=xlsread('bp_ga_samples1_copy_copy_new92.xlsx'); testData=xlsread('bp_ga_samples1_copy_copy_new10.xlsx'); lenTrain=length(trainData); lenTest=length(testData); TrainF=trainData(:,1:6); TrainL=trainData(:,7:9); TestF=testData(:,1:6); TestL=testData(:,7:9); model1=svmtrain(TrainF,TrainL(:,1)); model2=svmtrain(TrainF,TrainL(:,2)); model3=svmtrain(TrainF,TrainL(:,3)); predict1=svmclassify(model1,TestF); predict2=svmclassify(model2,TestF); predict3=svmclassify(model3,TestF); preTest=zeros(lenTest,3); preTest(:,1)=predict1; preTest(:,2)=predict2; preTest(:,3)=predict3; j=0; for i=1:lenTest if preTest(i,:)==TestL(i,:) j=j+1; end end ACY=j/lenTest; end