Building a k-Nearest Neighbor algorithm with the Iris dataset | MATLAB

%Code:

clc

clear all

close all

warning off

load fisheriris

x=meas(:,3);

y=meas(:,4);

c=species;

output=[];

m=c;

k=input('Enter the k value');

ersa=input('Enter number of test datapoints:');

for i=1:ersa

a=input('Enter the first parameter value of the test:');

b=input('Enter the second parameter value of the test:');

distance=[];

for i=1:length(x)

    e=sqrt((x(i)-a)^2+(y(i)-b)^2);

    distance=[distance e];

end

temp=0;

gemp=0;

for i=1:length(distance)

    for j=1:(length(distance)-i)

        if(distance(j)>distance(j+1))

            temp=distance(j);

            distance(j)=distance(j+1);

            distance(j+1)=temp;

            gemp=c{j};

            c{j}=c{j+1};

            c{j+1}=gemp;

        end

    end

end

classy={};

for i=1:k

    classy{i}=c{i};

end

tabulate(classy);

classy=string(classy);

output=[output mode(classy)];

c=m;

end