Machine learning: Clustering and classification on the campaign trail

As the election season rampages on, we categorize voters into broad demographics -- soccer moms, NASCAR dads, blacks, whites, ALICEs, yuppies -- in an attempt to understand and discuss this complex, churning electorate. In doing so we're tapping into something fundamental about how we perceive the world: not as a sequence of singular individuals, but rather as a massive set of overlapping taxonomies that, taken together, comprise an impressively structured human experience. With fewer than 20 yes/no queries on category membership we can often identify a single object amidst a staggering breadth of possibilities. We've grouped everything that we know to exist and the groupings themselves are the primary subject of our thoughts. We can go the other direction as well -- taking an object and placing it in its many groups.