finding classifier performance in MATLAB
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I want to classify the breast cancer dataset using SVM.
I divide the 569 instances into 5 sets of data and groups, then use classperf function to compute the performance, but I don't know what arguments are to be given in classperf function. Pls help me.
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clc;clf;clear all;close all;
data=xlsread('DATACANCER.XLSX');
load clasy;
i=24;
j=25;
data = [data(:,i), data(:,j)];
A1= data(1:113,:);A2=data(114:226,:);A3=data(227:340,:);A4=data(341:454,:);A5=data(455:569,:);
groups = ismember(species,'B');
[train, test] = crossvalind('holdOut',groups,0.2);
G1=groups(1:113,:);G2=groups(114:226,:);G3=groups(227:340,:);G4=groups(341:454,:);G5=groups(455:569,:);
cp = classperf(groups);
figure
svmStruct = svmtrain(A1,G1,'showplot',true);
title(sprintf('Kernel Function: %s',...
func2str(svmStruct.KernelFunction)),...
'interpreter','none');
classes = svmclassify(svmStruct,A2,'showplot',true);
classperf(cp,classes,----);<--------HERE IS MY DOUBT
ans1=cp.CorrectRate*100;
disp(ans1);
cp
figure
svmStruct = svmtrain(A2,G2,'showplot',true);
title(sprintf('Kernel Function: %s',...
func2str(svmStruct.KernelFunction)),...
'interpreter','none');
classes = svmclassify(svmStruct,A3,'showplot',true);
classperf(cp,classes,----);<--------HERE IS MY DOUBT
ans2=cp.CorrectRate*100;
disp(ans2);
cp
figure
svmStruct = svmtrain(A3,G3,'showplot',true);
title(sprintf('Kernel Function: %s',...
func2str(svmStruct.KernelFunction)),...
'interpreter','none');
classes = svmclassify(svmStruct,A4,'showplot',true);
classperf(cp,classes,--------);<--------HERE IS MY DOUBT
ans3=cp.CorrectRate*100;
disp(ans3);
cp
figure
svmStruct = svmtrain(A4,G4,'showplot',true);
title(sprintf('Kernel Function: %s',...
func2str(svmStruct.KernelFunction)),...
'interpreter','none');
classes = svmclassify(svmStruct,A5,'showplot',true);
classperf(cp,classes,-------);<--------HERE IS MY DOUBT
ans4=cp.CorrectRate*100;
disp(ans4);
cp
figure
svmStruct = svmtrain(A5,G5,'showplot',true);
title(sprintf('Kernel Function: %s',...
func2str(svmStruct.KernelFunction)),...
'interpreter','none');
classes = svmclassify(svmStruct,A1,'showplot',true);
classperf(cp,classes,-------);<--------HERE IS MY DOUBT
ans5=cp.CorrectRate*100;
disp(ans5);
cp
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