Wnb

- Add unit tests for `GaussianWNB`
- Refactor and minor improvements in `GaussianWNB`

- Test whether the `GeneralNB` estimator adheres to scikit-learn conventions
- Convert some hidden methods to internal methods
- Fix classifiers in _setup.py_
- Add pypi build badge to README

- `np.mean()` is replaced with `np.average()` to estimate the expected value of normal distribution
- Finding classes and their count is done first in the `fit` method
- Minor change in error messages

- Rename `priors_` to `class_prior_` in `GeneralNB` and `GaussianWNB` classes
- Remove `ddof=1` while calculating standard deviation for normal distribution
- Fix a critical bug in calculating log probability in `GeneralNB` class
- Add a _tests_ directory with some unit tests for `GeneralNB`

- Add `_support` attribute and `support` property to `DistMixin` to indicate the support of the probability distribution
- Add `_check_support` internal method that checks if a given value lies within the support of the distribution, and if not, shows a warning
- Set `_type` attribute for `ContinuousDistMixin` and `DiscreteDistMixin` to "continuous" and "discrete", respectively
- Set the support of all the distribution classes in `wnb.dist` module in their `_support_` attribute

- Add a parent mixin `DistMixin` for continuous and discrete distribution mixin
- Restructure `ContinuousDistMixin` and `DiscreteDistMixin` by inherting from `DistMixin`
- Add `get_params()` method to distribution mixins to return the distribution parameters
- Add a common `__repr__` method to distribution mixins