the k-NN Classifier ```matlab k = 5; % Number of neighbors knnModel = fitcknn(X_train, Y_train, 'NumNeighbors', k); ``` 3. Making Predictions and Evaluating Performance ```matlab Y_pred = predict(knnModel, X_test); % Confusion matrix confMat = confusionm
sets include Yale, ORL, and AT&T face datasets. Preprocessing Steps: Convert images to grayscale (if not already) Resize images to uniform dimensions Flatten images into vectors Normalize pixel values for consistency Sample MATLAB code for data loading and preprocessing: ```matlab % Specify
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