1. A computer implemented method comprising: receiving a velocity distribution for a road segment, wherein the velocity distribution includes a plurality of velocity intervals, and, for each velocity interval, a count of how many velocity observations have a velocity measurement within the velocity interval, wherein each velocity observation has one or more features describing conditions under which the velocity observation was made; generating a mixture model having K component distributions, including generating a respective component distribution for each of one or more segments of the velocity distribution, wherein each velocity observation in the velocity distribution is assigned to one of the K component distributions; generating a decision tree, wherein the decision tree has a plurality of leaves, each leaf corresponding to one of the K component distributions, wherein a path from a root of the decision tree to each leaf represents a particular set of one or more features for the road segment; generating a rule from a particular leaf of the decision tree, wherein the rule maps one or more features for the road segment to one of the K component distributions according to a path from the root of the decision tree to the particular leaf, wherein the path corresponds to the one or more features for the road segment; and using, by a traffic data server implementing a predictive model that is configured to predict traffic behavior for a given road segment based on one or more features of the given road segment, the rule to predict traffic behavior for the road segment given one or more features for the road segment.