  This study proposes a novel framework based on the RuleFit method to estimate
Heterogeneous Treatment Effect (HTE) in a randomized clinical trial. To achieve
this, we adopted S-learner of the metaalgorithm for our proposed framework. The
proposed method incorporates a rule term for the main effect and treatment
effect, which allows HTE to be interpretable form of rule. By including a main
effect term in the proposed model, the selected rule is represented as an HTE
that excludes other effects. We confirmed a performance equivalent to that of
another ensemble learning methods through numerical simulation and demonstrated
the interpretation of the proposed method from a real data application.
