1. A machine-readable, non-transitory storage medium encoded with instructions that, when executed by one or more processors, cause the one or more processors to carry out a process for generating directions for use in navigation during a current driving session, the process comprising: receiving a target destination; generating at least one candidate route; probabilistically determining that one of a plurality of conditional variant models associated with a target attribute corresponds to a condition of the target attribute, the plurality of conditional variant models learned from previous user driving sessions; scoring the at least one candidate route using the determined conditional variant model; providing a scored route to a user; detecting a change in the condition of the target attribute, wherein the detecting a change in the condition of the target attribute comprises: recomputing probabilities for the conditional variant models associated with the target attribute periodically during the current driving session using subsequently observed data of the current driving session; and probabilistically determining that a second conditional variant model currently corresponds to the condition of the target attribute; and providing an altered route to the user based on the detected change.
1. A machine-readable, non-transitory storage medium encoded with instructions that, when executed by one or more processors, cause the one or more processors to carry out a process for generating directions for use in navigation during a current driving session, the process comprising: receiving a target destination; generating at least one candidate route; probabilistically determining that one of a plurality of conditional variant models associated with a target attribute corresponds to a condition of the target attribute, the plurality of conditional variant models learned from previous user driving sessions; scoring the at least one candidate route using the determined conditional variant model; providing a scored route to a user; detecting a change in the condition of the target attribute, wherein the detecting a change in the condition of the target attribute comprises: recomputing probabilities for the conditional variant models associated with the target attribute periodically during the current driving session using subsequently observed data of the current driving session; and probabilistically determining that a second conditional variant model currently corresponds to the condition of the target attribute; and providing an altered route to the user based on the detected change. 2. The machine-readable, non-transitory storage medium of claim 1 , the process further comprising: determining a driver ID for the current driving session; and restricting the plurality of conditional variant models associated with the target attribute to include only conditional variant models associated with the driver ID.