# transform data points transformedIn=featureTransform(numPoints, pointsIn) transformedOut=featureTransform(numPoints, pointsOut) transformedAll=np.concatenate((transformedIn,transformedOut),axis=0) #print transformedAll #print yAll print "Trained:" print "--------" # learn w maxEpoches=1000 # increase this value and you get better results. But you have to wait 3 days for it ... w=perco.perco(transformedAll,yAll,maxEpoches) print 'w= ', np.ndarray.tolist(w) # test how good our classifier works ... okCtr=0 nokCtr=0 for i in range(0,2*numPoints): x=np.reshape(transformedAll[i,:],[np.size(transformedAll,1),1]) classified=perco.classify(x,w) if yAll[i] == classified: okCtr=okCtr+1 else: nokCtr=nokCtr+1 # plot statictis ...
