1. A method comprising: generating a first density model that approximates value densities in a set of data, wherein the first density model comprises a first set of functional components; selecting a first functional component of the first set of functional components based at least in part on how much the first functional component contributes to how well the first set of functional components approximates the value densities in the set of data; generating a second density model comprising a second set of functional components, wherein the second set of functional components includes at least one more functional component than the first set of functional components, and wherein the second set of functional components is determined using at least the first functional component and a variation of the first functional component as seed components; storing, in association with the set of data, a resulting density model that is generated based at least in part on the steps of generating the first density model, selecting the first functional component, and generating the second density model; wherein the method is performed by one or more computing devices.