def train(self,maxiter=100,threshold=0.1): v,self.T=eig(self.L) #print v self.km=KMEANSC(self.T[:,1:self.K].transpose(),self.K) self.km.train(maxiter,threshold) self.labels=self.km.labels
[18.75,9.8], [18.9,10.35], [18.9,11.05], [18.8,12.15], [18.3,12.65], [17.8,13.4], [16.95,14.15], [16.1,14.8], [14.8,15.35], [13.55,15.35], [11.6,15], [10.4,14.25], [11.3,14.4], [12.2,15.15], [12.45,15.35], [13.05,15.4], [13.85,15.25]] ).transpose() a=KMEANSC(features,2) a.train(180) print a.result() for i in range(features.shape[1]): if a.labels[i]==0: plt.plot(features[0][i],features[1][i],'or') elif a.labels[i]==1: plt.plot(features[0][i],features[1][i],'ob') else: plt.plot(features[0][i],features[1][i],'oy') plt.show() #print a.result() #print a.bfWhiteCen()
