3. The machine-readable medium of claim 2 wherein learning conditional variants comprises determining if at least one of an explicit and implicit condition applies to a particular conditional variant of a model.
9. The machine-readable medium of claim 3 wherein for both explicit and implicit conditions applying to a particular conditional variant of a model, learning conditional variants further comprises: partitioning attribute data computed for one or more road segments from a plurality of driving sessions into appropriate data buckets by explicit conditions; and clustering attribute data within a data bucket based on a similarity metric to form implicit conditional variants within each explicit condition.