simulate k nearest neighbourhood
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Hi,
I want to simulate knn. When I add a new point on graph where other data points are on, it can predict class of it, but I don't have any idea about what to do after I upload a data set.
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KSSV
2019년 7월 4일
Play with this:
x = rand(500,1) ; y = rand(500,1) ;
l = kmeans([x y],4) ;
figure
hold on
scatter(x,y,50,l,'o','filled')
N = 10 ;
for i = 1:100
% pick any point
[ptx,pty] = getpts() ;
idx = knnsearch([x y],[ptx pty],'k',N)' ;
li = mean(l(idx)) ;
text(ptx,pty,num2str(li))
plot(ptx,pty,'*r')
plot([ptx*ones(N,1) x(idx)]',[pty*ones(N,1) y(idx)]','r')
end
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KSSV
2019년 7월 5일
The result is correct in given code......code is showing up different groups/ labels. Attach your data and code to rectify the error.
KSSV
2019년 7월 5일
Why/how for loop is a trianing? For knnsearch there wont be any training. It gets the specififed number of nearest neighbors by calculating distances.
That line of plot is to show up lines joining the picked point and it's neighbors.
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