How to show hyperplane in SVM for multiclass classification(fitcecoc)

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X=a(:,2:3);
Y=a(:,1);%classes
figure
gscatter(X(:,1),X(:,2),Y);
xlabel('Petal Length (cm)');
ylabel('Petal Width (cm)');

t = templateSVM( 'KernelFunction', 'linear', 'Standardize', true);

Mdl = fitcecoc( X,Y,'Learners', t);
    
%% Now I need the hyperplanes for the above multiclass classification
%

Now I need the hyperplanes for the above multiclass classification showing data saperation,

Answer 1

[Abhaya]

Hi Sanjib,

I understand you want to create a visualization of the hyperplanes for the multiclass classification to illustrate the separation of the data.

To achieve this, you can follow the steps given below.

• Create a grid of points for plotting the decision boundary

[x1Grid, x2Grid] = meshgrid(linspace(min(X(:, 1)), max(X(:, 1)), 500), linspace(min(X(:, 2)), max(X(:, 2)), 500));

XGrid = [x1Grid(:), x2Grid(:)];

• Predict the class for each point in the grid

predictedLabels = predict(SVMModel, XGrid);

• Reshape the predictions to match the grid size

predictedLabels = reshape(predictedLabels, size(x1Grid));

• Plot the decision boundaries

hold on;
contour(x1Grid, x2Grid, predictedLabels, 'LineWidth', 1, 'LineColor', 'k');
hold off;

For more information, please refer to following MATLAB documentations on ‘meshgrid’ function and ‘contour’ function.

• https://www.mathworks.com/help/matlab/ref/meshgrid.html
• https://www.mathworks.com/help/matlab/ref/contour.html

Additionally, you may refer to the following MATLAB community discussion for additional techniques on visualizing multiclass SVM decision boundaries.

https://www.mathworks.com/matlabcentral/answers/412365-how-to-find-the-multi-class-hyperplane-decision-boundaries-using-support-vector-machines-svm

Hope this solves your query.