write an image classification code in matlab in matlab

Here is a simple code for image classification using Support Vector Machines (SVM) in MATLAB:

main.m
% Load the dataset
load fisheriris

% Extract features
X = meas(:,3:4);

% Create target vector
target = categorical(species);

% Train the SVM
SVMModel = fitcsvm(X,target);

% Plot the SVM boundary
figure
gscatter(X(:,1),X(:,2),target)
hold on
Mdl = fitcsvm(X,target);
margin = 1/sqrt(sum(Mdl.Beta.^2));
f(x)=-(Mdl.Bias+Mdl.Beta(1)*x)/Mdl.Beta(2);
h = ezplot(f,[0 7 0 3]);
h.Color = 'r';
h.LineWidth = 2;
axis([0 7 0 3])
legend({'setosa','versicolor','SVM boundary'},'Location','southeast')
hold off

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In this example, meas contains the measurements of the iris flowers, X is the feature matrix with petal length and width as the features, species is the categorical target vector, and SVMModel is the fitted SVM model. The SVM boundary is plotted using gscatter and ezplot functions.

This is a simple example and the classification accuracy can be improved by using more features and more sophisticated algorithms.

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