K-Nearest Neighbors visualization | MATLAB

Problem Statement:
Provide an example of a training set such that the same unknown sample can be classified in different ways if k is set to 1 or 3.

%Code:

clc

clear all

close all

warning off

output=[];

x=[1 3 0 -1 0];

y=[0 0 0 0 2];

c=["CA","CA","CB","CB","CB"];

m=c;

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

es=input('For how many times you want to run the code:');

xg=[];

yg=[];

for erts=1:es

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

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

xg=[xg a];

yg=[yg b];

distance=[];

for i=1:length(x)

    e=sqrt((x(i)-a)^2+(y(i)-b)^2);

    distance=[distance e];

end

distance

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=[classy c(i)];

end

output=[output mode(classy)];

c=m;

end

sty=[];

for i=1:length(c)

if (c(i)=="CA")

    sty=[sty "b+"];

else

    sty=[sty "r*"];

end

end

for i=1:length(c)

    plot(x(i),y(i),sty(i),'linewidth',5);

    hold on;

end

for i=1:length(xg)

    plot(xg(i),yg(i),'ko','linewidth',5);

end