how to find accuracy using multiple value of k in knn classifier (matlab)

Question

I use knn classifier to classify images according to their writers (problem of writer recognition). I worked on a given database that contains 150 images with 100 images for training and 50 images for testing. I use this code to find the accuracy of the classifier( k=1):

load('testdirection.mat') 
load('traindirection.mat')
load('testlabels.mat') 
load('trainlabels.mat') 
class = knnclassify(testdirection,traindirection, trainlabels);
cp = classperf(testlabels,class);
cp.CorrectRate 
fprintf('KNN Classifier Accuracy: %.2f%%\n',100*cp.CorrectRate )

I want to find different accuracy for different value for k [1..25] and save result in matrix matlab. I want also to plot the result to see the variability of accuracy depending on the value of k. Please, help me to change this code and thanks in advance

hbaderts hbaderts · Accepted Answer · 2015-02-13T14:04:08

knnclassify has an optional fourth argument k which is the number of nearest neighbors. You can just put the knnclassify in a for loop and iterate through all values for k.

load('testdirection.mat') 
load('traindirection.mat')
load('testlabels.mat') 
load('trainlabels.mat') 

for k=25:-1:1
    class = knnclassify(testdirection,traindirection, trainlabels, k);
    cp = classperf(testlabels,class);
    correctRate(k) = cp.CorrectRate;
end

You can plot the result e.g. using stem or plot

stem(1:25,correctRate);

PS: note that according to the MATLAB documentation, knnclassify will be removed in a future release and you should better use fitcknn.

how to find accuracy using multiple value of k in knn classifier (matlab)

1 Answers