Major Refactor + Added metrics

[zStupan]

This pull request closes #25

Summary

• Transactions in the dataset are now stored directly as a pandas DataFrame (removed self.data / renamed it to transactions).
• Added metrics: 'lift', 'coverage', 'rhs_support', 'conviction', 'interestingness', 'comprehensibility', 'netconf', 'yulesq'
• Renamed 'shrinkage' to 'amplitude'
• Renamed 'coverage' to 'inclusion'
• Deleted the AssociationRule class
• Moved the computation of metrics from the AssociationRule class to the Rule class. The metrics can still be accessed as properties of Rule, e.g. rule.support.
• Moved rule building functionalities from the AssociationRule class to the NiaARM class.
• Changed rule building: antecedent and consequent are now lists of Feature objects, where min_val and max_val are the bounds of the attribute as decided by the solution vector, and for categorical attributes, categories is set to a list containing a single selected category.
• Changed the interface of the NiaARM class as discussed in the linked issue, metrics can now be passed as a dict of pairs {metric_name: weight} or a sequence of metric names, in which case, all the corresponding weights will be set to 1.
• Added a repr method to the Feature class which replaces _fix_borders and format_rules
• Updated tests accordingly.
• Cleaned up the code.

[firefly-cpp]

This is amazing @zStupan! No major issues at all.

Things to consider in future iterations:

• add a reference for each metric in order to allow other researchers to explore ideas behind metrics,
• update docs with mathematical formulas of metrics (one table?).