Mabwiser

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major:
- Breaking: Updated NumPy RNG backend to utilize the new Generator class. This is a breaking change for algorithms with random components.
- Updated NumPy version dependency to >=1.17.0 to reflect the utilization of the new Generator class.

minor:
- Added multivariate sampling to base RNG class
- Updated multivariate sampling logic in LinTS to utilize updated NumPy RNG backend

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major:
- New Algorithm: TreeBandit as a decision-tree based neighborhood policy.
- Many thanks to irmakbky for her contribution!
- See also Elmachtoub, A. N., et. al. "A practical method for solving contextual bandit problems using decision trees". UAI 2017

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minor:
- Updated dtype from np.int to int in base_mab.py line 294 to resolve deprecation warning from numpy>=1.20.0
- Updated sklearn version dependency to >=0.24.0 because of changes in the KMeans implementation

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minor:
- Internal variable rename for LSHNearest
- Clarifications to LSHNearest docstring

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major:
- New Algorithm: Locality Sensitive Hashing Approximate Nearest Neighbors
- This neighborhood policy uses locality-sensitive hashing with random projection via the SimHash algorithm to create approximate neighborhoods.
- More information: https://en.wikipedia.org/wiki/Locality-sensitive_hashing#Random_projection

minor:
- Refactor of _Neighbors and _Radius classes to support reusability of empty neighborhood functionality
- Switch to centralized version incrementing and use of the opensourcefmr.com email

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major:
- Initial release on PyPi.org

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