if we run the code rattlesnake animal('rattlesnake'[ , , , , ]boa animal('boa\nconstrictor'[ , , , , ]dartfrog animal('dart frog'[ , , , , ]animals [rattlesnakeboadartfrogcompareanimals(animals it produces figure containing the table as you probably expectedthe distance between the rattlesnake and the boa constrictor is less than that between either of the snakes and the dart frog noticeby the waythat the dart frog does seem to be bit closer to the rattlesnake than to the boa nowlet' add to the bottom of the above code the lines alligator animal('alligator'[ , , , , ]animals append(alligatorcompareanimals(animals it produces the table perhaps you're surprised that the alligator is considerably closer to the dart frog than to either the rattlesnake or the boa constrictor take minute to think about why the feature vector for the alligator differs from that of the rattlesnake in two placeswhether it is poisonous and the number of legs the feature vector for the alligator differs from that of the dart frog in three placeswhether it is poisonouswhether it has scalesand whether it is cold-blooded yet according to our distance metric the alligator is more like the dart frog than like the rattlesnake what' going onthe root of the problem is that the different features have different ranges of values all but one of the features range between and but the number of legs ranges from to this means that when we calculate the euclidean distance the number of legs gets disproportionate weight let' see what