Rules generation

This plugin provides the ability to extract a set of interpretable rules from a Random Forest. The approach is based on the article “Learning accurate and interpretable models based on regularized random forests regression“.

Plugin Information

How To Use

You first need to set some general parameters: target, type of prediction, metric to optimize, performance drop threshold …
Next there are two parameters for the algorithm:

• Number of clauses in a rule: the longer the rule, the more accurate it is, but the less generalizable it is. Behind the scene, this is the max_depth of the random forest.
• Regularisation parameters: to filter out noisy rules, we use Lasso. This is the alpha parameter of Lasso.

Finally, using the min support parameter, you can also choose to precise that all rules below a certain support threshold are not interesting.