Interpretable Two-level Boolean Rule Learning for Classification

Understand

This paper proposes algorithms for learning two-level Boolean rules in Conjunctive Normal Form (CNF, i.e.

• AND-of-ORs) or Disjunctive Normal Form (DNF, i.e.
• OR-of-ANDs) as a type of human-interpretable classification model, aiming for a favorable trade-off between the classification accuracy and the simplicity of the rule.
• Two formulations are proposed.