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hello every body i have an error ??? Error: File: test.m Line: 31 Column: 3 exactely in [~,scores] = predict(cl,xGrid); i have Matlab 7.8.0 (R2009a)
- rand(1); % For reproducibility
- r = sqrt(rand(100,1)); % Radius
- t = 2*pi*rand(100,1); % Angle
- data1 = [r.*cos(t), r.*sin(t)]; % Points
- r2 = sqrt(3*rand(100,1)+1); % Radius
- t2 = 2*pi*rand(100,1); % Angle
- data2 = [r2.*cos(t2), r2.*sin(t2)]; % points
- figure;
- plot(data1(:,1),data1(:,2),'r.','MarkerSize',15)
- hold on
- plot(data2(:,1),data2(:,2),'b.','MarkerSize',15)
- ezpolar(@(x)1);ezpolar(@(x)2);
- axis equal
- hold off
- data3 = [data1;data2];
- theclass = ones(200,1);
- theclass(1:100) = -1;
- %Train the SVM Classifier
- cl = fitcsvm(data3,theclass,'KernelFunction','rbf',...
- 'BoxConstraint',Inf,'ClassNames',[-1,1]);
- % Predict scores over the grid
- d = 0.02;
- [x1Grid,x2Grid] = meshgrid(min(data3(:,1)):d:max(data3(:,1)),...
- min(data3(:,2)):d:max(data3(:,2)));
- xGrid = [x1Grid(:),x2Grid(:)];
- [~,scores] = predict(cl,xGrid);
- % Plot the data and the decision boundary
- figure;
- h(1:2) = gscatter(data3(:,1),data3(:,2),theclass,'rb','.');
- hold on
- ezpolar(@(x)1);
- h(3) = plot(data3(cl.IsSupportVector,1),data3(cl.IsSupportVector,2),'ko');
- contour(x1Grid,x2Grid,reshape(scores(:,2),size(x1Grid)),[0 0],'k');
- legend(h,{'-1','+1','Support Vectors'});
- axis equal
- hold off
回答 (1 件)
Steven Lord
2017 年 11 月 10 日
The ability to ignore specific input or output arguments in function calls using the tilde operator was introduced in release R2009b. Replace ~ with a dummy variable name, like dummy, for older releases.
3 件のコメント
per isakson
2017 年 11 月 11 日
fitcsvm - Train binary support vector machine classifier
fitcsvm trains or cross-validates a support vector machine (SVM)
model for two-class (binary) classification on a low- through
moderate-dimensional predictor data set. fitcsvm supports...
Documentation > Statistics and Machine Learning Toolbox > Classification > Support Vector Machine Classification
Walter Roberson
2017 年 11 月 11 日
That routine was introduced in R2014a.
In your software release there was no built-in SVM in any toolbox, so people would compile and link the third party libsvm
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