fix kernel kmeans

Author: sth4nth

chapter06/knGauss.m

@@ -8,7 +8,7 @@
 %   K: nx x ny kernel matrix
 % Written by Mo Chen ([email protected]).
 if nargin < 3
-    s = 1;
+    s = 0.4;
 end
 
 if nargin < 2 || isempty(Y)  

chapter06/knKmeans.m

@@ -1,4 +1,4 @@
-function [label, energy] = knKmeans(K, init)
+function [label, model, energy] = knKmeans(X, init, kn)
 % Perform kernel kmeans clustering.
 % Input:
 %   K: n x n data matrix
@@ -10,6 +10,7 @@
 % Reference: Kernel Methods for Pattern Analysis
 % by John Shawe-Taylor, Nello Cristianini
 % Written by Mo Chen ([email protected]).
+K = kn(X,X);
 n = size(K,2);
 if numel(init)==1
     k = init;
@@ -26,4 +27,8 @@
     [val, label] = max(T-dot(T,E,2)/2,[],1);
 end
 energy = trace(K)-2*sum(val); 
+model.kn = kn;
+model.label = label;
+model.X = X;
+
 

demo/ch06/knKmeans_demo.m

@@ -5,8 +5,8 @@
 n = 200;
 [X, y] = kmeansRnd(d,k,n);
 init = ceil(k*rand(1,n));
-K = knLin(X,X);
-label = knKmeans(K,init);
+
+label = knKmeans(X,init,@knLin);
 
 label0 = kmeans(X,init);
 maxdiff(label,label0)
@@ -17,7 +17,6 @@
 X = [x1,x1+pi/2;
     x2,-x2];
 
-K = knGauss(X,X,0.4);
-label = knKmeans(K,2);
+label = knKmeans(X,2,@knGauss);
 figure;
 plotClass(X,label);