wehub-resource-sync
31 lines
1.0 KiB
Matlab
Executable File
31 lines
1.0 KiB
Matlab
Executable File
function [label, mu, energy] = kmeans(X, m)
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% Perform kmeans clustering.
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% Input:
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% X: d x n data matrix
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% m: initialization parameter
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% Output:
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% label: 1 x n sample labels
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% mu: d x k center of clusters
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% energy: optimization target value
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% Written by Mo Chen (sth4nth@gmail.com).
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label = init(X, m);
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n = numel(label);
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idx = 1:n;
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last = zeros(1,n);
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while any(label ~= last)
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[~,~,last(:)] = unique(label); % remove empty clusters
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mu = X*normalize(sparse(idx,last,1),1); % compute cluster centers
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[val,label] = min(dot(mu,mu,1)'/2-mu'*X,[],1); % assign sample labels
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end
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energy = dot(X(:),X(:),1)+2*sum(val);
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function label = init(X, m)
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[d,n] = size(X);
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if numel(m) == 1 % random initialization
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mu = X(:,randperm(n,m));
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[~,label] = min(dot(mu,mu,1)'/2-mu'*X,[],1);
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elseif all(size(m) == [1,n]) % init with labels
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label = m;
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elseif size(m,1) == d % init with seeds (centers)
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[~,label] = min(dot(m,m,1)'/2-m'*X,[],1);
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end |