mabwiser
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[IJAIT 2021] MABWiser: Contextual Multi-Armed Bandits Library
Hi team, I am working on Contextual MAB, and though the example mentions "subscriber" as 0,1. But I was curious to know if I could use a different categorical variable,...
Encompasses the minimal amount of changes needed to integrate Spock. Unit tests adjusted for all changes. 100% pass. The only fundamental change to the API is that TreeBandit parameters are...
Line 242 of mabwiser.linear.py ``` python arm_expectations[nonrandom_indices] = np.array([self.arm_to_model[arm].predict(nonrandom_context) for arm in arms]).T ``` if there is an epsilon > 0, and low numbers of context provided can result in...
Hi, thanks for the excellent **mabwiser** package! I’m experimenting with delayed rewards and have noticed that some MAB algorithms show bias when selecting between equivalent arms, i.e., when splitting ties....
Hello! Thanks for this nice project! I'm currently integrating mabwiser into my project. I have the situation that in given contexts certain arms are not applicable and shouldn't be considered...
How can i visualise the arms for each different algorithm to monitor this in production?