In this paper, parameter identification using interpretable machine learning and quality engineering is applied to a shaking table test data of a full-scale 5-story wooden structure. The following results are shown; 1) By the parameter identification for detailed analysis model, good agreement with experimental result is obtained. 2) It was confirmed that the difference between the analytical results and the experimental results becomes smaller when the capacity of some walls and other elements was increased.
