quick look at machine learning def readmammaldata(fnamescale)"""assumes scale is boolean if truefeatures are scaled""#start of code is same as in previous version #use featurevals to build list containing the feature vectors #for each mammal scale featuresif needed if scalefor in range(numfeatures)featurevals[iscalefeatures(featurevals[ ]#remainder of code is the same as in previous version def testteeth(numclustersnumtrialsscale)featureslabelsspecies =readmammaldata('dentalformulas txt'scaleexamples buildmammalexamples(featureslabelsspecies#remainder of code is the same as in the previous version figure code that allows scaling of features when we execute the code print 'cluster without scalingtestteeth( falseprint '\ncluster with scalingtestteeth( trueit prints cluster without scaling cowelkmoosesea lion herbivores carnivores omnivores badgercougardogfoxguinea pigjaguarkangaroominkmolemouseporcupinepigrabbitraccoonratred batskunksquirrelwoodchuckwolf herbivores carnivores omnivores beardeerfur sealgrey sealhumanlion herbivores carnivores omnivores cluster with scaling cowdeerelkmoose herbivores carnivores omnivores guinea pigkangaroomouseporcupinerabbitratsquirrelwoodchuck herbivores carnivores omnivores badgerbearcougardogfoxfur sealgrey sealhumanjaguarlionminkmolepigraccoonred batsea lionskunkwolf herbivores carnivores omnivores