Rulekit

* Updated criteria in regression and survival contrast sets.
* Some other fixes.

Contrast set-related updates:
* Fixed time measurement.
* Metainduction with multiple `minsupp_all` values.
* Update of three data sets so they can be properly read in scipy.
* Toy example results updated
* Parameter names consistent with contrast set manuscript.

Many new features and improvements:
* Induction of contrast sets for clasiffication, regression, and survival data (`contrast_attribute` tag in XML data set description),
* Penalties for reusing attributes, rewards for covering new examples (`penalty_strength` and `penalty_saturation` parameters),
* Complementary conditions (`complementary_conditions` parameter ),
* Multiple covering passes (`max_passes_count` parameter),
* Possibility to ignore selected attributes (`ignore` tag in XML data set description),
* Model can be saved in tabular form with some useful statistics (`model_csv` tag in XML data set description),
* Parameter `min_rule_covered` renamed to `mincov_new`, automatic decision if value is absolute ( >= 1) or relative ( < 1),
* Several other paremeters added (`mincov_all`, `max_neg2pos`),
* Improved selection of best condition in growing,
* Very verbose mode.

* Improved computational performance for classification problems.
* Multiple bugs fixed.
* Basic CI added.