wehub-resource-sync
38 lines
975 B
Matlab
Executable File
38 lines
975 B
Matlab
Executable File
function [label, model, energy] = knKmeans(X, init, kn)
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% Perform kernel kmeans clustering.
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% Input:
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% K: n x n kernel matrix
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% init: either number of clusters (k) or initial label (1xn)
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% Output:
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% label: 1 x n sample labels
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% model: trained model structure
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% energy: optimization target value
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% Reference: Kernel Methods for Pattern Analysis
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% by John Shawe-Taylor, Nello Cristianini
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% Written by Mo Chen (sth4nth@gmail.com).
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n = size(X,2);
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if numel(init)==1
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k = init;
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label = ceil(k*rand(1,n));
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elseif numel(init)==n
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label = init;
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end
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if nargin < 3
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kn = @knGauss;
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end
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K = kn(X,X);
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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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E = sparse(last,1:n,1);
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E = E./sum(E,2);
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T = E*K;
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[val, label] = max(T-dot(T,E,2)/2,[],1);
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end
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energy = trace(K)-2*sum(val);
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if nargout == 3
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model.X = X;
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model.label = label;
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model.kn = kn;
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end
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