# Confusion Matrix of SVM

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Lana Aydin on 4 Nov 2020
Commented: Lana Aydin on 10 Nov 2020
Hello
I would like to ask about how to find the valure of Linear, Gaussian, Poly = 2, Poly = 3 for dataset of iris
I used the code bellow it runs without problem but I don't know how to calculate the value of them
t = templateSVM('Standardize',true,'BoxConstraint',100,'KernelFunction','linear','KernelScale','auto');
Mdl = fitcecoc(dataTrain(:,2:4),dataTrain.Species,'Learners',t);
Predictions_SVM_Linear = predict(Mdl,dataTest(:,2:4));
figure;
C_SVM_Linear = confusionmat(dataTest.Species,Predictions_SVM_Linear);
cm_SVM_Linear = confusionchart(C_SVM_Linear,{'Iris-setosa','Iris-versicolor','Iris-virginia'});
cm_SVM_Linear.Title = 'Iris Classification Using Linear SVM';
cm_SVM_Linear.RowSummary = 'row-normalized';
cm_SVM_Linear.ColumnSummary = 'column-normalized';

Pranav Verma on 10 Nov 2020
Hi Baraah,
From your question I understand that you want to use Linear, Gaussian and Polynomial Kernel functions in templateSVM function. You can use the following name, value pairs for these:
• 'KernelFunction','gaussian'
• 'KernelFunction','linear'
• 'KernelFunction','polynomial','PolynomialOrder',2 (for polynomial of order '2')
For further information on the Kernel Functions, please refer to the below documentation:
Thanks
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Lana Aydin on 10 Nov 2020
Ok thank you Pranav, I will check it out. Thanks again.