Xgboost-distribution

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- Added more precise loss description, negative log likelihood vs error
- Various updates to conform with xgboost==1.6.0 release

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- Added type hints to XGBDistribution model class
- Hotfix to add error raising if sample weights are used (which is not yet implemented)

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- Hot fix to enable compatibility with xgboost v1.5.0 (enable_categorical kwarg)

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- Fixed the objective parameter in trained model to be reflective of distribution
- Support for model saving and loading with pickle (please don't use pickle)
- Added count data example with distribution heatmap, :issue:`45`
- Updated docs to include estimators parameter, :issue:`43`
- Implemented cleaner model saving, tests against binary and json formats

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- Performed experiments on various datasets to assess XGBDistribution performance
- Added exponential distribution
- Added Laplace distribution

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- Added poisson distribution
- Added negative-binomial distribution
- Changed naming conventions of distributions
- Safety checks on distribution parameters