[bahro]

"When we started the training process, many of us thought that the “fingerprint” feature described above would be the “silver bullet” that would crack the problem for us. We were surprised to note that this wasn’t the case at all — in fact, it was features based on the dispersion of parking locations that turned out to be one of the most powerful predictors of parking difficulty."

I assume dispersion of parking locations is the distance from parking location to destination? I would have liked to see more about what kinds of inputs they used and how they cleaned them up to account for the confounding factors they mention (public transit users, private parking.)

[feral]

> I assume dispersion of parking locations is the distance from parking location to destination?

I would guess its the density of parking locations in a given area, rather than distance to destination?