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Urban Start-up Agglomeration and Venture Capital Investment (view source)
Revision as of 13:53, 3 December 2020
, 13:53, 3 December 2020→Curvature
The curvature results seem somewhat better than the elbow results but are still far from ideal. Here are some things I look for and/or don't like in a layer selection method:
*Interior solutions are good, collapsing to the bounds, especially the lower bound is bad
*Stable interior solutions are better - when the results approximate a quadratic so that margins generally decrease and then increase around a maximum, the interior results are stable and that's very desirable
*Consistent solutions are good within cities - it's nice when adjacent years in the same city have more or less the same layer selected
*Consistent solutions across cities are also good - When the method picks roughly similar layer indicies (i.e., % unclustered) across cities, particularly conceptually similar cities, that's a plus
