Fair-scoring

Added
- Parameter `prefer_high_scores` to allow for both types of scores.
This allowed for shorter dataset handling of the COMPAS examples.
- Preparation to host docs on readthedocs.

Fixed

- Show correct project-link on [pypi.org](https://pypi.org/project/fair-scoring/)
- `README.md` shows the correct installation command

Added
- Bias Metric Classes for
- Calibration: `fairscoring.metrics.CalibrationMetric`
- Wasserstein Distance: `fairscoring.metrics.WassersteinMetric`
- ROC-base Metrics: `fairscoring.metrics.roc.ROCBiasMetric`
- Default Bias Metrics for
- Equal Opportunity: `fairscoring.metrics.bias_eo`
- Predictive Equality: `fairscoring.metrics.bias_pe`
- Calibration: `fairscoring.metrics.bias_cal`
- Independence: `fairscoring.metrics.bias_ind`
- ROC: `fairscoring.metrics.roc.bias_roc`
- xROC: `fairscoring.metrics.roc.bias_xroc`
- Experiments on
- Adult Dataset
- COMPAS Dataset
- German Credit Risk Dataset
- Tests for compatibility with results in the publication
- COMPAS Dataset