Add live data that feeds the Elo ratings
- You have an interesting source of live data.
- Or you want something predicted
- Publish live data on an ongoing basis
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This can help make the Elo ratings better.
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However only "live" data is ideal, to prevent algorithms from memorizing
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See instructions for publishing data at www.microprediction.com (maybe jump to https://www.microprediction.com/python-4). Basically what you need to do is set up a cron job or similar that periodically grabs a live data point and publishes it. First:
pip install microprediction from microprediction import new_key write_key = new_key(difficulty=12) # <--- Takes a long time, sorry
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Then your regular job can do the following:
from microprediction import MicroWriter
writer = MicroWriter(write_key=write_key)
writer.set(name='my_own_stream.json',value=3.14157) # <--- Must end in .json
This will create a stream like airport short term parking and a bunch of hungry time-series algorithms will come to it. The remainder of this note deals only with skater creation.
As noted, I try to jump on a Google Meet twice a week and the details are in the microprediction knowledge center. My arrival rate is higher on Fridays than Tuesdays :)
I'm not so good at scheduling calls outside of these times and frankly that tends to be counter to my productivity anyway. So just jump on some Tuesday night or Friday noon if you are keen to contribute to this package, or anything else that relates to open source community prediction.
