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Predicting Crime in Portland – data from the trenches
- stabiilize 9y agojust skimming through, it looks like she's using past data to try to predict the future (call time and location, etc) this seemed flawed from the start it is an interesting project though
- vikiomega9 9y agoThe aim of the challenge is to predict crime hotspots which for the most part don't vary much I'd think? The challenge then becomes identifying cluster density as a function of time which might mean using past data makes sense.
- rdtsc 9y agoWhy is it flawed. Crime hotspots are usually cyclical varying with seasons and weather like she points towards the end. There are other factors. You might be thinking of stock markets which is a different thing.
- DrScump 9y agoDoesn't that assume a stable population and a consistent economy?
- __Julia 9y agoI couldn't understand the argument, can you elaborate with some technical/scientific references ? P.S: I am not the OP
- gadjo95 9y agoI hope they are thinking of the shortcomings of doing that: https://motherboard.vice.com/en_us/article/mg7w4x/canada-hub-and-cor-policing-privacy-police https://motherboard.vice.com/en_us/article/mg7w4x/canada-hub...
- rdtsc 9y agoGood idea on using weather and holidays. I played with a similar dataset from local police for a machine learning class. And I remember how hotspots movement was correlated with seasons.
- __Julia 9y ago> POIs are tagged with user-generated category tags such as “Amenity,” “Hotel,” “Shop,” “Restaurant,” “Mailbox,” etc. We found 11,000 labeled points of interest in Portland in the 2016 dataset. Did you use the API or the shape file in here ? Can you share the list of relevant Census feature to get the names, re-writing them from the picture takes time.