Rulekit

Update in `preferredAttributesPerRule`/`preferredConditionsPerRule` parameters: the value of 0 interpreted as the infinity.

Removed unnecessary thread pool analyzing different decision classes.

* Fixed bug in expert rules pruning.
* Two-sided intervals counted as a single condition instead of two.

* Classification:
* Significantly faster growing (two orders of magnitude for sets with >100k instances), faster pruning,
* Added approximate mode (`approximate_induction` parameter). Note: this is an experimental feature - the results may change in future releases.
* Regression:
* Mean-based growing set as default (few times faster then median, non-significant impact on accuracy).
* Survival:
* Faster growing and pruning (few fold improvement).

Changes from the previous release:
* Added fast induction of regression rules based on mean instead of median (`mean_based_regression`),
* Added boolean parameter for disabling apriori precision control (`control_apriori_precision`).