0.14.0 - 2022-10-26

• Introducing the bandit module for running multi-armed bandits
• Introducing the sketch module with summarization tools and data sketches working in a streaming fashion!

bandit

• Added bandit.EpsilonGreedy.
• Added bandit.UCB.
• Added bandit.ThomsonSampling.
• Added a bandit.base module.
• Added bandit.envs.CandyCaneContest, which implements the Gym interface.
• Added bandit.envs.KArmedTestbed, which implements the Gym interface.
• Added bandit.evaluate for basic benchmarking of bandit policies on a Gym environment.

drift

• Exposed more parameters in ADWIN: clock, max_buckets, min_window_length, and grace_period.

model_selection

• Added model_selection.BanditRegressor, which is a generic model selection method that works with any bandit policy.
• Removed model_selection.EpsilonGreedyRegressor due to the addition of model_selection.BanditRegressor.
• Removed model_selection.UCBRegressor due to the addition of model_selection.BanditRegressor.

proba

• Added proba.Beta.
• Added a sample method to each distribution.
• Added a mode property to each distribution.
• Replaced the pmf and pdf methods with a __call__ method.

sketch

• Moved misc.Histogram to sketch.Histogram.
• Moved stats.LossyCount to sketch.HeavyHitters and update its API to better match collections.Counter.
• Added missing return self in HeavyHitters.
• Added the Count-Min Sketch (sketch.Counter) algorithm for approximate element counting.
• Added an implementation of Bloom filter (sketch.Set) to provide approximate set-like operations.