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View Code? Open in Web Editor NEWA multi-armed bandit library for Python
License: MIT License
A multi-armed bandit library for Python
License: MIT License
slots.py:377: RuntimeWarning: invalid value encountered in true_divide sum(self.pulls) * np.max(np.nan_to_num(self.wins / self.pulls))
Options:
Refactor to historical and future payouts for both fixed payout values (both binary and numerical) and variable payouts.
This probably requires a relatively significant API change.
Remove explicit support for Python 2.7 and 3.4
We need tests!
Running
mab = slots.MAB()
mab.run()
results in an error.
This seems to be due to how the defaults are handled for a "live" trial.
live=False
might be a better default?
I want to be sure that the current implementation of the Bayesian bandits works if the payouts are arbitrary sizes, rather than just the default 0 or 1.
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