
You Are (Probably) Here: Better Map Pins with DBSCAN and Random Forests - mcenedella
https://engineering.foursquare.com/you-are-probably-here-better-map-pins-with-dbscan-random-forests-9d51e8c1964d
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mcenedella
“the catch is that the distribution of check-in densities in the real world
varies greatly as a function of venue shape and size, which in turn are a
function of category or chain, and location. So, the check-ins at a suburban
Target look very different from the check-ins at a bar in Manhattan. There is
no single value of MinPts and Eps that would work globally.”

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kankroc
To anyone reading this who wants to try DBSCAN, give its more recent brother
HDBSCAN a go. The H stands for hierarchical and it's way better when dealing
with clusters that aren't very similar (think big vs small).

There's an excellent pip package that seamlessly integrates woth scikit-learn
too!

