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Old 06-13-2017, 10:45 AM   #9
DeltaLover
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Quote:
Originally Posted by lamboy View Post
ML is indeed difficult to apply to handicapping especially since flow and trips need to be taken into account -- however, these factors are so subjective. Take other fields where ML systems are applied and experts all say it requires SMEs to interpret the data.

At the end, imho, an ensemble method of algorithms work ok but more importantly a good visualation tool works best. After all--aren't the bris,timeform and drf pps nothing more than data dashboards?
The difficulty lies in the problem definition more than anything else. One of the core challenges has to do with the representation of the primitive handicapping factors along with the derived metrics and their through time and circuit behavior.
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